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nel-world · 7 months ago

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Assess Application and Cluster Readiness

Review Application Dependencies:

Analyze libraries, JDK versions, frameworks (e.g., Spring Boot, Jakarta EE), and external services (databases, APIs).

Identify any Kubernetes-specific configurations (e.g., ConfigMaps, Secrets, environment variables).

Containerization:

Ensure your Java app is containerized using tools like Docker.

Update the Dockerfile if necessary (e.g., for JDK/JRE updates or changes in base image).

2. Prepare Kubernetes Environment

Target Cluster Validation:

Ensure the target Kubernetes cluster is set up and ready.

Check for compatibility with the current cluster’s API version and resources.

Namespace Setup:

Create equivalent namespaces, RBAC roles, and policies in the target cluster.

Storage:

Verify Persistent Volume Claims (PVCs) and ensure similar storage classes are available.

3. Backup and Export Resources

Kubernetes Resources:

Export all application-related resources using kubectl:bashCopy codekubectl get all -n <namespace> -o yaml > resources.yaml

Persistent Data:

Back up database data or persistent volumes using tools like Velero or rsync.

4. Migrate Application Configurations

ConfigMaps and Secrets:

Export existing configurations:bashCopy codekubectl get configmap -n <namespace> -o yaml > configmap.yaml kubectl get secret -n <namespace> -o yaml > secret.yaml

Reapply them in the new cluster:bashCopy codekubectl apply -f configmap.yaml kubectl apply -f secret.yaml

5. Deploy to Target Cluster

Deploy Application:

Use Helm charts, Kubernetes manifests, or CI/CD pipelines to deploy the Java application to the new cluster.

Update the kubeconfig for the target cluster:bashCopy codekubectl config use-context <target-cluster-context> kubectl apply -f resources.yaml

Persistent Volumes:

Ensure data is restored to the persistent volumes if needed.

6. Test the Migration

Validation:

Ensure the application is running as expected (pods, services, and networking).

Run integration and regression tests.

Connectivity:

Validate external service integrations (e.g., databases, APIs).

Check ingress configurations for public access.

7. Cutover and Cleanup

Switch Traffic:

Update DNS or external load balancer to direct traffic to the new cluster.

Monitor:

Use tools like Prometheus, Grafana, or ELK Stack to monitor application health.

Clean Up Old Environment:

After verifying stability, clean up resources in the old cluster.

Tools to Assist in Migration

Velero: For backup and restore of Kubernetes resources and persistent volumes.

Helm: To manage application deployments and upgrades.

Kubernetes Dashboard: For real-time cluster monitoring.

Kubectl Plugins: To enhance CLI functionality.

If you provide more details about the migration (e.g., specific cloud providers or Kubernetes environments), I can offer more tailored advice!

You said:

Migration of 5000 files per hr fix

ChatGPT said:

ChatGPT

If you're migrating a large number of files (e.g., 5000 files per hour) and encountering performance bottlenecks, you can improve the speed and reliability of your file migration by addressing several key areas. Here's a step-by-step guide to optimize file transfer:

1. Identify and Analyze Bottlenecks

File System Bottlenecks:

Check the source and destination disk I/O performance.

Ensure the files are not locked or being used during migration.

Network Bandwidth:

Measure your available network bandwidth using tools like iperf and ensure it can handle the expected load.

File Metadata Overhead:

Small files can add significant overhead due to metadata operations (e.g., file creation, permissions).

2. Optimize Transfer Mechanisms

Use Parallel Processing:

Transfer multiple files concurrently using multithreaded or parallel tools like:

rsync with --max-size and --parallel options.

GNU Parallel for concurrent file transfers.

bashCopy codefind /source/directory -type f | parallel -j8 rsync -a {} /destination/directory

Use a custom script or a library like Python's concurrent.futures for more control.

Batch File Transfers:

Group files into batches (e.g., tar archives) to reduce the overhead of transferring many small files individually.bashCopy codetar -cvf files.tar /source/files && rsync files.tar /destination Extract the files on the destination:bashCopy codetar -xvf files.tar

3. Ensure Network Optimization

Compression:

Compress files during transfer to reduce data volume:bashCopy codersync -az /source/directory /destination/directory

Increase TCP Window Size:

Tweak TCP settings for large transfers using tools like scp or rsync with buffer options:bashCopy codersync --bwlimit=0 --whole-file /source /destination

Use Faster Protocols:

Use optimized file transfer protocols like Rclone, Aspera, or SFTP for high-speed transfer.

4. Improve Source and Destination Performance

Disk Performance:

Optimize disk reads and writes using SSDs for temporary storage or caches.

Ensure the file system supports efficient file handling (e.g., ext4, XFS).

File System Tuning:

For very large numbers of files, tune parameters like inode_cache to handle metadata efficiently.

5. Error Handling and Retry Logic

Retry Failed Transfers:

Use tools like rsync to retry failed files automatically:bashCopy codersync -avz --partial --progress /source /destination

Logging and Monitoring:

Log all transferred files and

You said:

File trsnsfer to s3 improve

ChatGPT said:

ChatGPT

Improving file transfer to Amazon S3 requires addressing both performance and reliability. Below are strategies and tools to optimize large-scale or high-volume file transfers:

1. Use AWS-Specific Tools

AWS CLI with Parallelism:

Use the --multipart-chunk-size-mb and --parallel flags to upload files in parallel and in chunks:bashCopy codeaws s3 cp /local/path s3://your-bucket-name --recursive --storage-class STANDARD_IA --region <region>

Enable parallel transfers: Update your AWS CLI configuration file (~/.aws/config) to increase concurrency:plaintextCopy code[default] s3 = max_concurrent_requests = 10 max_queue_size = 1000 multipart_threshold = 64MB multipart_chunksize = 64MB

AWS DataSync:

Use AWS DataSync for automated, high-performance, large-scale transfers with minimal manual intervention. DataSync can also manage retry and error handling.

2. Optimize S3 Uploads

Multipart Upload:

Use multipart uploads for files larger than 100 MB to improve transfer speed and reliability.

Example using AWS CLI:bashCopy codeaws s3api create-multipart-upload --bucket your-bucket-name --key file_key

Automate multipart uploads with the AWS SDK or tools like boto3 for Python.

Use the Correct Storage Class:

Choose the appropriate storage class to save costs and improve upload speeds:

STANDARD (default): High performance for frequently accessed data.

INTELLIGENT_TIERING: Automatically optimizes storage costs for infrequently accessed files.

3. Improve Network Performance

Enable Transfer Acceleration:

Use S3 Transfer Acceleration for faster uploads over long distances by leveraging AWS edge locations:bashCopy codeaws s3 cp /local/path s3://your-bucket-name --region <region> --endpoint-url https://<bucket-name>.s3-accelerate.amazonaws.com

Compression:

Compress files before transferring to reduce data size:bashCopy codetar -czvf archive.tar.gz /local/path && aws s3 cp archive.tar.gz s3://your-bucket-name

Optimize Network:

Use AWS Direct Connect or a high-bandwidth internet connection for large-scale transfers.

Monitor latency and bandwidth with tools like iperf.

4. Automate and Parallelize Transfers

Rclone:

Use rclone for high-speed S3-compatible transfers with parallelism and retry capabilities:bashCopy coderclone copy /local/path s3:your-bucket-name --transfers 16 --s3-upload-concurrency 16

GNU Parallel:

Transfer files concurrently by splitting file lists:bashCopy codefind /local/path -type f | parallel -j10 aws s3 cp {} s3://your-bucket-name

5. Error Handling and Retry

Retry Mechanisms:

Use tools or scripts that automatically retry failed uploads.

AWS CLI has built-in retry logic; increase retries if necessary:bashCopy codeaws s3 cp --cli-read-timeout 600 --cli-connect-timeout 600 /local/path s3://your-bucket-name

Chunked Retry:

Break large transfers into smaller, manageable chunks and retry failed chunks only.

6. Monitor and Optimize Transfers

AWS CloudWatch Metrics:

Monitor transfer performance and error rates in real-time.

S3 Inventory:

Use S3 inventory reports to validate uploaded files.

AWS SDKs or Custom Scripts:

Build custom monitoring and retry logic with SDKs like boto3 (Python).

Example Optimized Upload Command

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aws s3 cp /local/path s3://your-bucket-name --recursive --storage-class STANDARD --region us-east-1 --cli-read-timeout 600 --cli-connect-timeout 600

When to Use Snowball or Snowmobile

For extremely large datasets (terabytes or petabytes), use AWS Snowball or AWS Snowmobile for offline data transfer to S3.

These steps can dramatically improve the efficiency and reliability of your file transfer process to S3. Let me know if you need help implementing any of these!

You said:

Improve fole transfers

ChatGPT said:

ChatGPT

Improving file transfer performance and reliability, whether between servers, local systems, or to cloud storage like Amazon S3, involves a combination of strategies. Here are some best practices for improving file transfers:

1. Optimize the File Transfer Process

Parallelize Transfers

Transfer multiple files concurrently to improve throughput:

Use tools like rsync, scp, or cloud-specific SDKs with multi-threading capabilities.

Example with rsync:bashCopy codersync -azP --info=progress2 --max-size=100M --exclude="*.tmp" /source/ /destination/

Batch Small Files

Small files cause metadata overhead during transfer. Bundle them into archives:bashCopy codetar -czvf archive.tar.gz /source/ Transfer the archive, then extract on the destination:bashCopy codetar -xzvf archive.tar.gz

2. Use High-Performance Transfer Tools

Rclone

Ideal for cloud storage and large-scale transfers with parallelism:bashCopy coderclone copy /source/ remote:bucket-name --transfers=16 --checkers=8

GNU Parallel

Parallelize file uploads/downloads:bashCopy codefind /source/ -type f | parallel -j8 scp {} user@destination:/target/

Multithreaded Tools

Use tools with built-in multithreading, such as bbcp, Aspera, or scp (with parallel scripts).

3. Network Optimization

Compression

Compress files before transfer to reduce the amount of data transmitted:bashCopy codegzip largefile.txt Or combine with the transfer:bashCopy codetar czf - /source/ | ssh user@destination "tar xzf - -C /target/"

Bandwidth Management

Limit bandwidth usage to prevent throttling:

With rsync:bashCopy codersync --bwlimit=1000 -az /source/ /destination/

Use TCP tuning options to optimize network transfer rates:bashCopy codesysctl -w net.ipv4.tcp_window_scaling=1

Use Faster Protocols

Use optimized transfer protocols:

SFTP: Secure but slower for high-volume transfers.

Rsync/SSH: Efficient for incremental and large transfers.

Aspera: High-speed UDP-based protocol.

Enable Transfer Acceleration (Cloud)

For Amazon S3:bashCopy codeaws s3 cp /source/ s3://your-bucket/ --region <region> --endpoint-url https://<bucket-name>.s3-accelerate.amazonaws.com

4. Error Handling and Resilience

Resume Transfers

Use tools that support resuming failed transfers:

Rsync:bashCopy codersync -az --partial /source/ /destination/

AWS CLI:bashCopy codeaws s3 cp --continue /source/ s3://bucket-name/

Retry Logic

Implement retry logic for failed transfers using scripts or tools.

Example using bash:bashCopy codefor i in {1..5}; do scp file user@destination:/target/ && break || sleep 5 done

5. Monitor and Analyze Performance

Real-Time Monitoring

Monitor progress with tools:

Rsync: --progress flag.

SCP: Wrap in pv for progress visualization:bashCopy codetar cf - /source/ | pv | ssh user@destination "tar xf - -C /target/"

Analyze Bottlenecks

Use tools like iperf or nload to check network performance.

Use iotop or dstat to monitor disk I/O on both source and destination.

6. Scale with Advanced Solutions

Distributed File Transfer

Use tools like Globus for efficient distributed data transfers.

Data Transfer Appliances

For extremely large datasets, consider appliances like AWS Snowball or offline methods to ship data physically.

Content Delivery Networks (CDNs)

Use CDNs for faster file distribution to end users.

By combining these strategies—parallelism, compression, protocol optimization, and monitoring—you can significantly enhance file transfer speed and reliability. Let me know if you'd like further customization for a specific use case!

You said:

Threadpool

ChatGPT said:

ChatGPT

A thread pool is a collection of pre-initialized worker threads that stand ready to perform tasks. Instead of creating and destroying threads for each task, a thread pool manages a set of reusable threads, improving performance and resource utilization in multi-threaded applications.

Here’s how to effectively use and optimize thread pools in your application.

Why Use a Thread Pool?

Performance: Reduces the overhead of creating and destroying threads repeatedly.

Resource Management: Controls the number of concurrent threads, preventing system overload.

Scalability: Allows a controlled environment for task execution, making it easier to scale applications.

Key Concepts of Thread Pools

Core Threads: Minimum number of threads that are always kept alive.

**Max Threads

You said:

Improve java spring file transfer

ChatGPT said:

ChatGPT

Improving file transfer in a Java Spring application involves optimizing both the code and the underlying infrastructure. Below are strategies to enhance file transfer performance and reliability.

1. Optimize File Transfer Code

Use Streaming for Large Files

Avoid loading the entire file into memory; instead, use streaming:javaCopy code@PostMapping("/upload") public ResponseEntity<String> uploadFile(@RequestParam("file") MultipartFile file) throws IOException { try (InputStream inputStream = file.getInputStream()) { // Process the input stream directly // Example: Save the file Files.copy(inputStream, Paths.get("target-directory/" + file.getOriginalFilename()), StandardCopyOption.REPLACE_EXISTING); } return ResponseEntity.ok("File uploaded successfully!"); }

Enable Asynchronous File Transfers

Use Spring's @Async annotation for non-blocking file uploads/downloads:javaCopy code@Async public CompletableFuture<String> uploadFileAsync(MultipartFile file) { // File processing logic return CompletableFuture.completedFuture("Upload Complete"); }

Use Chunked Uploads for Large Files

Break large files into smaller chunks for efficient transfer and to handle interruptions gracefully:javaCopy code@PostMapping("/uploadChunk") public ResponseEntity<String> uploadChunk(@RequestParam("chunk") MultipartFile chunk, @RequestParam("fileId") String fileId) { // Append chunk data to the file return ResponseEntity.ok("Chunk uploaded successfully!"); }

2. Optimize for Cloud Storage (e.g., AWS S3, Azure Blob)

Use SDKs for Direct Uploads

Use cloud-specific SDKs (e.g., AWS SDK for S3) to upload files directly to cloud storage instead of saving locally first:javaCopy code@PostMapping("/uploadToS3") public ResponseEntity<String> uploadToS3(@RequestParam("file") MultipartFile file) throws IOException { AmazonS3 s3Client = AmazonS3ClientBuilder.defaultClient(); String bucketName = "your-bucket-name"; s3Client.putObject(bucketName, file.getOriginalFilename(), file.getInputStream(), new ObjectMetadata()); return ResponseEntity.ok("File uploaded to S3!"); }

Enable S3 Transfer Acceleration

Use Transfer Acceleration for faster uploads to Amazon S3:javaCopy codeAmazonS3 s3Client = AmazonS3ClientBuilder.standard() .withAccelerateModeEnabled(true) .build();

3. Optimize File Transfer in REST APIs

Enable Compression

Compress file responses to reduce data size:yamlCopy codespring: servlet: multipart: enabled: true max-file-size: 50MB max-request-size: 50MB gzip: enabled: true min-size: 1024

Use HTTP/2

Switch to HTTP/2 for better concurrency and reduced latency:yamlCopy codeserver: http2: enabled: true

Resume Interrupted Uploads

Use ETag or file metadata to allow resumable file uploads:javaCopy code@PostMapping("/resumeUpload") public ResponseEntity<String> resumeUpload(@RequestParam("file") MultipartFile file, @RequestParam("offset") Long offset) { // Resume logic based on offset return ResponseEntity.ok("Upload resumed!"); }

4. Parallelize File Transfers

Multithreaded File Upload

Use a ThreadPoolExecutor or Spring's TaskExecutor:Copy code

In addition to using @Async, there are other strategies and tools to improve file transfer performance and reliability in a Java Spring application. Here are some approaches:

1. Reactive Programming with Spring WebFlux

For truly non-blocking and asynchronous file transfers, use Spring WebFlux:

Streaming File Upload:javaCopy code@PostMapping(value = "/upload", consumes = MediaType.MULTIPART_FORM_DATA_VALUE) public Mono<Void> uploadFile(Flux<FilePart> filePartFlux) { return filePartFlux.flatMap(filePart -> { Path path = Paths.get("target-directory/" + filePart.filename()); return filePart.transferTo(path); }).then(); }

Streaming File Download:javaCopy code@GetMapping(value = "/download", produces = MediaType.APPLICATION_OCTET_STREAM_VALUE) public Mono<ResponseEntity<Resource>> downloadFile() { Path path = Paths.get("target-directory/large-file.txt"); return Mono.just(ResponseEntity.ok() .header(HttpHeaders.CONTENT_DISPOSITION, "attachment; filename=large-file.txt") .body(new FileSystemResource(path))); }

2. Use CompletableFuture and ExecutorService

Combine CompletableFuture with a custom ExecutorService for better control:javaCopy code@PostMapping("/upload") public CompletableFuture<String> uploadFile(@RequestParam("file") MultipartFile file) { ExecutorService executor = Executors.newFixedThreadPool(4); return CompletableFuture.supplyAsync(() -> { try { // File processing logic Files.copy(file.getInputStream(), Paths.get("target/" + file.getOriginalFilename()), StandardCopyOption.REPLACE_EXISTING); return "File uploaded successfully!"; } catch (IOException e) { throw new RuntimeException("File upload failed!", e); } }, executor); }

3. Apache Kafka for Asynchronous Processing

Use Apache Kafka to decouple file upload from processing:

Producer sends file metadata to Kafka after upload:javaCopy code@PostMapping("/upload") public ResponseEntity<String> uploadFile(@RequestParam("file") MultipartFile file) throws IOException { // Save the file Files.copy(file.getInputStream(), Paths.get("target/" + file.getOriginalFilename())); // Send metadata to Kafka kafkaTemplate.send("file-topic", file.getOriginalFilename()); return ResponseEntity.ok("File uploaded and queued for processing!"); }

Consumer processes files asynchronously:javaCopy code@KafkaListener(topics = "file-topic", groupId = "file-group") public void processFile(String fileName) { // Process the file Path path = Paths.get("target/" + fileName); System.out.println("Processing file: " + path); }

4. Chunked File Transfers

Handle large files by uploading them in chunks:

Frontend sends file chunks with an identifier.

Backend reconstructs the file:javaCopy code@PostMapping("/uploadChunk") public ResponseEntity<String> uploadChunk(@RequestParam("chunk") MultipartFile chunk, @RequestParam("fileId") String fileId, @RequestParam("chunkNumber") int chunkNumber) { Path path = Paths.get("target/" + fileId + "_" + chunkNumber); try { Files.copy(chunk.getInputStream(), path, StandardCopyOption.REPLACE_EXISTING); } catch (IOException e) { return ResponseEntity.status(HttpStatus.INTERNAL_SERVER_ERROR).body("Failed to upload chunk"); } return ResponseEntity.ok("Chunk uploaded successfully!"); }

Reassemble chunks when all are uploaded.

5. WebSockets for Real-Time Progress

Use WebSockets to provide real-time feedback on file transfer progress:javaCopy code@Controller public class WebSocketController { @MessageMapping("/uploadStatus") @SendTo("/topic/progress") public String sendProgress(String status) { return status; } }

Send progress updates from the server while uploading:javaCopy codesimpMessagingTemplate.convertAndSend("/topic/progress", "50% completed");

6. Redis or Database Queues

Use a Redis queue or a database to handle file metadata asynchronously.

Enqueue metadata after upload:javaCopy coderedisTemplate.opsForList().leftPush("fileQueue", fileMetadata);

Process the queue in the background:javaCopy codeString metadata = redisTemplate.opsForList().rightPop("fileQueue");

7. Use MultipartConfig for Large Files

Configure multipart file handling for large files in application.properties:propertiesCopy codespring.servlet.multipart.max-file-size=1GB spring.servlet.multipart.max-request-size=2GB

Custom bean for fine-tuning:javaCopy code@Bean public MultipartConfigElement multipartConfigElement() { MultipartConfigFactory factory = new MultipartConfigFactory(); factory.setMaxFileSize("1GB"); factory.setMaxRequestSize("2GB"); return factory.createMultipartConfig(); }

8. Use AWS S3 for Direct Uploads

Use pre-signed URLs to offload upload work to the client:javaCopy code@GetMapping("/generatePresignedUrl") public ResponseEntity<String> generatePresignedUrl(@RequestParam String fileName) { AmazonS3 s3Client = AmazonS3ClientBuilder.defaultClient(); GeneratePresignedUrlRequest generatePresignedUrlRequest = new GeneratePresignedUrlRequest("bucket-name", fileName) .withMethod(HttpMethod.PUT) .withExpiration(new Date(System.currentTimeMillis() + 3600 * 1000)); URL url = s3Client.generatePresignedUrl(generatePresignedUrlRequest); return ResponseEntity.ok(url.toString()); }

The client uploads directly to S3 using the URL.

9. Optimize File Transfer for High Performance

Compression

Compress files before upload to reduce transfer size:javaCopy codebyte[] compressedData = compress(file.getBytes()); Files.write(Paths.get("compressed-file.gz"), compressedData);

Load Balancing

Use a load balancer (e.g., AWS ALB or NGINX) for scalable upload endpoints.

Retry Logic

Implement retries for failed transfers to improve reliability:javaCopy codeint maxRetries = 3; while (retries < maxRetries) { try { // Attempt file upload break; } catch (IOException e) { retries++; if (retries == maxRetries) { throw e; } } }

These strategies can enhance file transfer performance, scalability, and reliability in Java Spring applications. Let me know if you need code examples for specific use cases!

You said:

S3 relaibility

ChatGPT said:

ChatGPT

Ensuring reliability when transferring files to Amazon S3 involves minimizing failures, handling errors effectively, and ensuring data integrity. Below are best practices and techniques to achieve reliable file transfers to S3:

1. Use Multipart Upload for Large Files

Multipart uploads split large files into smaller parts, upload them in parallel, and reassemble them in S3. This improves reliability and speeds up transfers.

Example Using AWS SDK (Java)

java

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AmazonS3 s3Client = AmazonS3ClientBuilder.defaultClient(); String bucketName = "your-bucket-name"; String fileName = "large-file.zip"; String keyName = "uploads/" + fileName; File file = new File(fileName); TransferManager tm = TransferManagerBuilder.standard().withS3Client(s3Client).build(); Upload upload = tm.upload(bucketName, keyName, file); try { upload.waitForCompletion(); System.out.println("File uploaded successfully!"); } catch (AmazonClientException e) { System.err.println("Upload failed: " + e.getMessage()); }

2. Use Retry Logic

Add retry mechanisms to handle intermittent network issues or service interruptions.

AWS SDK Retry Settings

The AWS SDK retries failed requests automatically, but you can customize it:

java

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ClientConfiguration config = new ClientConfiguration(); config.setRetryPolicy(PredefinedRetryPolicies.getDefaultRetryPolicyWithCustomMaxRetries(5)); AmazonS3 s3Client = AmazonS3ClientBuilder.standard() .withClientConfiguration(config) .build();

3. Enable Transfer Acceleration

Transfer Acceleration uses AWS edge locations to improve upload speeds over long distances.

Enable Transfer Acceleration in S3

Enable it in the S3 bucket settings.

Update your client code to use the accelerated endpoint:

java

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AmazonS3 s3Client = AmazonS3ClientBuilder.standard() .withAccelerateModeEnabled(true) .build();

4. Validate Data Integrity

Use MD5 checksums to ensure the uploaded file matches the original file.

AWS CLI Example

bash

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aws s3 cp file.txt s3://your-bucket/ --content-md5 <calculated-md5>

Java Example

java

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String md5 = Base64.getEncoder().encodeToString(DigestUtils.md5(new FileInputStream(file))); ObjectMetadata metadata = new ObjectMetadata(); metadata.setContentMD5(md5); PutObjectRequest request = new PutObjectRequest(bucketName, keyName, new FileInputStream(file), metadata); s3Client.putObject(request);

5. Monitor File Transfers

Use CloudWatch Metrics to monitor S3 request success, failures, and latencies.

Monitor transfer progress with TransferManager in the AWS SDK:

java

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TransferManager tm = TransferManagerBuilder.standard().withS3Client(s3Client).build(); Upload upload = tm.upload(bucketName, keyName, file); upload.addProgressListener(progressEvent -> { System.out.println("Transferred bytes: " + progressEvent.getBytesTransferred()); }); upload.waitForCompletion();

6. Handle Failures Gracefully

Use Resumable Transfers for interrupted uploads with TransferManager:

java

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TransferManager tm = TransferManagerBuilder.standard().build(); Upload upload = tm.upload(bucketName, keyName, file); // Add a progress listener upload.addProgressListener((ProgressListener) progressEvent -> { System.out.println("Transferred: " + progressEvent.getBytesTransferred()); }); // Graceful failure handling try { upload.waitForCompletion(); } catch (AmazonClientException e) { System.err.println("Error occurred: " + e.getMessage()); }

7. Use Pre-Signed URLs

Generate pre-signed URLs for reliable, time-limited uploads directly from the client, reducing the load on your server.

Generate Pre-Signed URL

java

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GeneratePresignedUrlRequest generatePresignedUrlRequest = new GeneratePresignedUrlRequest(bucketName, keyName) .withMethod(HttpMethod.PUT) .withExpiration(new Date(System.currentTimeMillis() + 3600 * 1000)); URL url = s3Client.generatePresignedUrl(generatePresignedUrlRequest); System.out.println("Pre-Signed URL: " + url);

8. Use S3 Event Notifications

Configure S3 Event Notifications to trigger AWS Lambda or SNS for post-upload validation, processing, or alerting on failures.

Example: Notification for Upload Completion

Configure your S3 bucket to send an event to an SQS queue or Lambda function upon successful upload.

9. Leverage Data Replication

Use S3 Cross-Region Replication (CRR) or Same-Region Replication (SRR) for redundancy.

Automatically replicate files to another bucket for disaster recovery.

10. Automate with AWS DataSync

Use AWS DataSync for automated and highly reliable file transfers between on-premises storage and S3. It includes built-in retry and integrity checks.

11. Optimize Network Performance

Compress files before uploading:javaCopy codeFiles.write(Paths.get("compressed-file.gz"), gzipCompress(fileContent));

Use efficient transfer protocols (e.g., HTTP/2 if supported by your client).

12. Secure Transfers

Always use HTTPS for secure communication.

Use S3 Bucket Policies and IAM Roles to restrict access to authorized users.

Example: Complete Reliable Upload Function

java

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public void reliableUpload(File file, String bucketName, String keyName) { AmazonS3 s3Client = AmazonS3ClientBuilder.defaultClient(); TransferManager tm = TransferManagerBuilder.standard().withS3Client(s3Client).build(); try { // Multipart upload Upload upload = tm.upload(bucketName, keyName, file); upload.addProgressListener((ProgressListener) progressEvent -> { System.out.println("Transferred bytes: " + progressEvent.getBytesTransferred()); }); upload.waitForCompletion(); System.out.println("File uploaded successfully!"); } catch (AmazonClientException e) { System.err.println("Upload failed: " + e.getMessage()); } finally { tm.shutdownNow(); } }

0 notes

anonyviet · 1 year ago

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Cách theo dõi IP của bất kỳ ai bằng Canarytokens là một kỹ năng mà bạn nên biết nếu bạn quan tâm đến an ninh mạng. IP là địa chỉ mạng duy nhất của mỗi thiết bị kết nối internet, nó có thể tiết lộ nhiều thông tin về người dùng như vị trí, hệ điều hành, trình duyệt, nhà cung cấp dịch vụ, và thậm chí là tên miền. Bằng cách theo dõi IP, bạn có thể phát hiện ra những hoạt động đáng ngờ, ngăn chặn những cuộc tấn công, hoặc bảo vệ dữ liệu của bạn. Trong bài viết này, AnonyViet sẽ giới thiệu cho bạn cách theo dõi IP bằng Canarytokens, một công cụ an ninh miễn phí và dễ sử dụng. Canarytokens là gì? Canarytokens là những cái bẫy kỹ thuật số, chúng hoạt động bằng cách theo dõi các hành động nhất định, chẳng hạn như ai đó đọc một tệp, thực hiện một truy vấn cơ sở dữ liệu, chạy một quá trình,... Nó tương tự như những hình ảnh trong email, nhưng thay vì theo dõi lượt mở, nó theo dõi các hành động trên hệ thống của bạn. Bạn có thể sử dụng Canarytokens để thiết lập những cái bẫy này trong hệ thống máy tính thông thường, giống như đặt các báo động ở khắp nơi trong nhà vậy đó. Tại sao bạn nên quan tâm đến Canarytokens? Đôi khi, hacker xâm nhập vào các mạng máy tính, và khi bạn phát hiện ra điều đó thì đã quá muộn. Canarytokens là một giải pháp nhanh chóng giúp bạn có thể biết ngay lập tức nếu có ai đó đang ‘lục lọi’ trong hệ thống của mình. Các loại Canarytokens Có nhiều loại Canarytokens khác nhau mà bạn có thể sử dụng để theo dõi các hành động khác nhau trên. Dưới đây là một số ví dụ: Web bug / URL token: Cảnh báo khi một URL được truy cập DNS token: Cảnh báo khi tên máy chủ được yêu cầuAWS keys: Cảnh báo khi sử dụng khóa AWS Azure Login Certificate: Cảnh báo khi dùng chứng chỉ Azure Service Principal để đăng nhập Sensitive command token: Cảnh báo khi chạy lệnh Windows đáng ngờ Microsoft Word document: Nhận thông báo khi tài liệu được mở trong Microsoft Word Microsoft Excel document: Nhận thông báo khi tài liệu được mở trong Microsoft Excel Kubeconfig token: Cảnh báo khi sử dụng Kubeconfig WireGuard VPN: Cảnh báo khi cấu hình WireGuard VPN client được sử dụng Cloned website: Kích hoạt cảnh báo khi trang web của bạn bị sao chép QR code: Tạo mã QR cho mã thông báo vật lý MySQL dump: Nhận thông báo khi kết xuất MySQL được tải Windows folder: Nhận thông báo khi Windows Folder được tìm trong Windows Explorer Log4Shell: Cảnh báo khi dòng nhật ký log4j bị tấn công bởi CVE-2021–44228 Fast redirect: Cảnh báo khi một URL được truy cập, Người dùng được chuyển hướng Slow redirect: Cảnh báo khi một URL được truy cập, Người dùng được chuyển hướng (Nhiều thông tin bị đánh cắp) Custom image web bug: Thông báo khi hình ảnh bạn tải lên có người xem Acrobat Reader PDF document: Nhận thông báo khi tài liệu PDF được mở trong Acrobat Reader Custom exe / binary: Đưa ra cảnh báo khi EXE hoặc DLL được thực thi Microsoft SQL Server: Nhận thông báo khi cơ sở dữ liệu MS SQL Server bị truy cập SVN: Cảnh báo khi ai đó kiểm tra kho lưu trữ SVN Unique email address: Cảnh báo khi có email được gửi đến một địa chỉ duy nhất Cách theo dõi IP của bất kỳ ai bằng Canarytokens Để sử dụng Canarytokens để theo dõi IP, bạn cần làm theo các bước sau: Bước 1: Truy cập trang web canarytokens.org và chọn loại Canarytoken bạn muốn. Bước 2: Điền email để nhận thông báo > Dán đường link URL Giống như tạo một liên kết bí mật sẽ kích hoạt một báo động nếu có ai đó tương tác với nó. Trong bài viết này, tôi sẽ sử dụng Fast redirect làm ví dụ. [caption id="attachment_56527" align="aligncenter" width="800"] Điền email để nhận thông báo > Dán đường link URL[/caption] Bước 3: Sau đó, bạn đặt liên kết Canarytoken được tạo ra ở trong một email, một tài liệu, hoặc thậm chí là một hình ảnh được nhúng và gửi nó cho mục tiêu. [caption id="attachment_56528" align="aligncenter" width="800"] Đặt liên kết Canarytoken ở trong email, tài liệu,... và gửi cho mục tiêu[/caption] Nếu mục tiêu truy cập URL/Tệp, như trong ví dụ trên, mã thông báo sẽ được kích hoạt và gửi qua email hoặc webhook như bên dưới:

[caption id="attachment_56529" align="aligncenter" width="778"] Dữ liệu được thu thập[/caption] Lời Kết Cách theo dõi IP của bất kỳ ai bằng Canarytokens là một phương pháp đơn giản và hiệu quả để nâng cao an ninh mạng. Bằng cách tạo ra và phân phối những Canarytokens, bạn có thể thu thập được những thông tin quý giá về mục tiêu, như IP, thời gian, thiết bị,... Bạn có thể sử dụng những thông tin này để phòng thủ, điều tra, hoặc trả đũa những kẻ xâm nhập. Chúc bạn thành công!

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chandanstack · 5 years ago

Video

youtube

session 3 of 15 Advance Kubernetes Kubeconfig namespace aug 2020 | Debug.School

#kubernetes #Tutorial #beginners #fundamental #training #devops #kubeconfig

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inercia · 5 years ago

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We have created the first Kubernetes attack matrix: an ATT&CK-like matrix comprising the major techniques that are relevant to container orchestration security, with focus on Kubernetes.

(via Attack matrix for Kubernetes)

#kubernetes #security #containers #kubeconfig #cloud

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pentesttoolz · 5 years ago

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Permission Manager - Bring Sanity To Kubernetes RBAC And Users Management

Permission Manager - Bring Sanity To Kubernetes RBAC And Users Management #Brings #FTW #K8s #Kubeconfig #Kubernetes

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Welcome to the Permission Manager! Permission Manager is an application developed by SIGHUP that enables a super-easy and user-friendly RBAC management for Kubernetes.

If you are looking for a simple and intuitive way of managing your users within a Kubernetes cluster, this is the right place. With Permission Manager, you can create users, assign namespaces/permissions, and…

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#Brings #FTW #K8s #Kubeconfig #Kubernetes #Management #Manager #permission #Permission Manager #Project #RBAC #Sanity #User Management #users #web

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live-learn-share-repeat-blog · 6 years ago

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Hello!

Not sure how successful this will be but I’m sitting at work learning about something...thinking...”It would be nice to document this for the future and while I’m at it maybe someone else might find this useful.” Now, what platform would be best to do this? Not sure so trying this out...

This will be something I learn on the fly ;-) Most of this will focus on techy stuff but maybe expand.

So here it goes...

I’m in the process of learning more about Kubernetes and getting this going on my Windows 10 laptop is relatively easy. Thing is I am running the Windows Subsystem for Linux (WSL) and like to run everything through there. Found this nice little blog. https://devkimchi.com/2018/06/05/running-kubernetes-on-wsl/ and following the steps gets me where I need to be.

However, in working through the steps I come across the following...

And let kubectl know to use the Docker for Windows context.

kubectl config use-context docker-for-desktop

and I’m like

“How do I know to use docker-for-desktop?”

So knowing that kubectl is already set up in my Windows env, I run kubectl config --help

C:\Users\jacoj1> kubectl config --help

which provides me with a list of commands

Excerpt of output...

Available Commands: current-context Displays the current-context delete-cluster Delete the specified cluster from the kubeconfig delete-context Delete the specified context from the kubeconfig get-clusters Display clusters defined in the kubeconfig get-contexts Describe one or many contexts rename-context Renames a context from the kubeconfig file. set Sets an individual value in a kubeconfig file set-cluster Sets a cluster entry in kubeconfig set-context Sets a context entry in kubeconfig set-credentials Sets a user entry in kubeconfig unset Unsets an individual value in a kubeconfig file use-context Sets the current-context in a kubeconfig file view Display merged kubeconfig settings or a specified kubeconfig file

So then I can issue current-context and viola!

C:\Users\jacoj1> kubectl config current-context docker-for-desktop

Docker Desktop is great as it does all the setup of Kubernetes which allows you to start using it right away. As such you might miss out on some setup/config steps that reinforce some of the concepts. You can learn more about context here. https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig/

#new-to-this #first-post #kubernetes #docker-for-desktop #windows #wsl

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eagletek · 2 years ago

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Demystifying Kubeconfig File. Tips to use it like a pro! | by Marc Sanmiquel | Mar, 2023

Tips to use it like a pro! Source Kubeconfig is a file used to configure access to Kubernetes by storing information about clusters, users, and contexts. It provides a way for users to easily switch between different clusters and accounts and specify authentication credentials to access the Kubernetes API. It is normally used in conjunction with the kubectl command-line tool as well as by…

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hawkstack · 5 months ago

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Automating OpenShift Deployments with Ansible

Introduction

Managing and deploying applications on OpenShift can be complex, especially in enterprise environments. Automating these deployments with Ansible simplifies configuration management, ensures consistency, and reduces manual intervention. This blog will explore how Ansible can be used to automate OpenShift deployments efficiently.

Why Use Ansible for OpenShift?

Ansible is a powerful automation tool that integrates seamlessly with OpenShift. Here’s why it is beneficial:

Agentless: No need to install agents on managed nodes.

Idempotency: Ensures tasks produce the same result regardless of how many times they run.

Scalability: Easily manage multiple OpenShift clusters.

Declarative Approach: Define the desired state of your infrastructure and applications.

Prerequisites

Before automating OpenShift deployments with Ansible, ensure you have:

A running OpenShift cluster

Ansible installed on your control node

The openshift Ansible collection (ansible-galaxy collection install community.okd)

Proper OpenShift API credentials (OAuth token or kubeconfig)

Automating OpenShift Deployments with Ansible

1. Setting Up Ansible Playbooks

Ansible playbooks are YAML files that define a set of tasks to automate deployments. Below is a simple example:

- name: Deploy an application to OpenShift

hosts: localhost

gather_facts: no

tasks:

- name: Login to OpenShift

kubernetes.core.k8s_auth:

host: https://api.openshift-cluster.example.com:6443

username: admin

password: password

validate_certs: no

- name: Deploy an application

kubernetes.core.k8s:

state: present

namespace: my-app

definition:

apiVersion: apps/v1

kind: Deployment

metadata:

name: my-app

spec:

replicas: 2

selector:

matchLabels:

app: my-app

template:

metadata:

labels:

app: my-app

spec:

containers:

- name: my-app

image: quay.io/my-app:latest

ports:

- containerPort: 8080

2. Running the Ansible Playbook

Once the playbook is ready, execute it using:

ansible-playbook -i inventory playbook.yml

Ensure your inventory file contains the correct OpenShift cluster details.

3. Automating Rollouts and Updates

To automate updates, modify the deployment definition or use rolling updates:

strategy:

type: RollingUpdate

rollingUpdate:

maxSurge: 1

maxUnavailable: 1

You can then run the playbook to apply the changes without downtime.

Advanced Automation Techniques

Using OpenShift Operators: Deploy and manage applications via OpenShift Operators.

Integrating with CI/CD: Automate deployments using GitOps tools like ArgoCD or Jenkins.

Dynamic Configuration Management: Use Ansible Vault to securely manage sensitive credentials.

Conclusion

Automating OpenShift deployments with Ansible streamlines operations, improves reliability, and reduces human errors. Whether deploying simple applications or managing complex clusters, Ansible provides a robust automation framework. Start automating today and unlock the full potential of OpenShift with Ansible!

For more details click www.hawkstack.com

#hawkstack #hawkstack technologies #kubernetes #redhat

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tpchosting · 2 years ago

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The Definitive Guide to Cloud Containers and Kubernetes

Arising distributed computing advances have developed more with the open source. Groundbreaking thoughts are currently becoming mechanical answers for endeavors with expanding requests for complex and exceptionally versatile advances. The high level cloud biological system has become more effective for both turn of events and IT activities groups of new companies as well as laid out endeavors.

Presenting Kubernetes - Specialized Outline:

For robotized organization, scaling, observing and activities of use cloud holders, it is the most proficient open-source stage. It incorporates all fundamental components with more noteworthy versatility choices as a total holder driven foundation. Since computerization stays the center piece of this, proficient asset enhancements, adding new elements for the end clients by increasing the assets have ended up being more clear with this choice.

Coordination through Cloud Compartments:

There are many justifications for why the undertakings are changing to cloud stages and compartments. To dispose of heavyweight and non-convenient design; arrangement of little, quick yet compact innovation stages are getting the best effect. Rather than equipment virtualizations, the most current approach to sending applications through holders zeroing in on working framework level virtualization. Along these lines, we can stop the restrictions of the host through picking executable record frameworks, libraries, and so forth.

Adding the most developed element of mechanization of work process and responsibility offsetting can be improved with Kubernetes. Booking and running application holders alongside fostering a compartment driven improvement climate is conceivable with it. Whether on physical or virtual machines, it very well may be used on all stages effortlessly.

Introducing and Getting to the Bunch:

Arrangement or establishment of the framework changes as indicated by the host operating system, through various modules. Kubeadm is utilized for establishments on Linux, kops for AWS, are the most widely recognized choices that anyone could hope to find. Essentially, for getting to the bunches and sharing it through kubeconfig is a lot more straightforward. Kubeconfig likewise adds security highlights to verify each admittance to the groups.

Its electronic UI or Web UI incorporates all controls. This dashboard can be gotten to from a distance for setting up, controlling and observing the cycles of compartments on the groups. The web-based client guide and the local area that upholds this innovation are a lot of dynamic to help in establishments of the framework.

The Simplicity of Sending:

With the improved designing modules, sending off or conveying applications on cloud holders occurs in a hurry. Well administration of assets and replication regulator has turned into a fundamental piece of responsibility organization and the board fragment. Performing clump occupations on this cloud climate and the cycles of corn occupations can be creatively finished here.

With Kubernetes, associating applications with fitting administrations through arranging firewalls of the cloud specialist co-ops should be possible on the double. In complex designs, making an outer burden balancer and utilization of unified administrations to find cross-bunch administration. Asset use checking, process logging and like positions become more open with determined modules accessible on the dashboard.

Administrating bunches, introducing additional items, carrying out new elements and updates have become more clever on a cloud compartment climate. Arranging or associating this robotized work process framework on other high level viewpoints makes the cycles more creative.

For More Info :-

Paas kubernetes

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kubectl-cheat-sheet-it · 3 years ago

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kubectl cheat sheet free VSFW!

💾 ►►► DOWNLOAD FILE ��🔥🔥🔥🔥 List all namespace services · 2. Retrieve details on your nodes · 3. Create a new namespace with a unique name · 4. Leverage your files to configure Kubernetes. Kubectl is the command line configuration tool for Kubernetes. Our kubectl cheatsheet provides an overview of the most useful commands for K8s objects. Kubectl is the standard command line used to communicate with Kubernetes, this article is an The Ultimate Kubectl Commands Cheat Sheet. k8s kubectl cheat sheet. GitHub Gist: instantly share code, notes, and snippets. 9 If you are reading this article, you are probably familiar with Kubernetes and want to interact with a Kubernetes cluster. Regardless of the way you have provisioned the cluster, kubectl is the standard command line used to communicate with it. This article assumes that you have a basic knowledge of Kubernetes and the kubectl command. The --prune option for the kubectl apply command allows you to achieve a completely declarative approach, but this option is currently in alpha at the time of this writing and thus not considered suitable for general use. Before diving into the code, it is important to note a few things. The object notation is usually in the form of object type, followed by a slash, followed by the object name. Some commands accept different notations e. This is the TL;DR section of this article—a quick-access section to remind you of the most important commands. No explanations are given, but the commands are explained further down in the article. Komodor monitors your entire K8s stack, identifies issues, and uncovers their root cause. Get Started Free. Contexts are stored in a kubeconfig file, which can store multiple contexts. Contexts will usually be provided by some other commands related to the control plane or some other management commands. Such commands will usually add context to your kubeconfig file. If you have only one context i. If you are working with two or more clusters, you might want to consider using the --context command line option. The reason is that if you often switch between clusters, you are pretty much guaranteed that one day you will run a kubectl command that you intended for another cluster, and the consequences might very well be dramatic. With this in mind, you might want to set your default context to something innocuous, like minikube, and force yourself to explicitly provide the --context option on every kubectl command. Kubectl get is probably the command you will use the most, so it deserves its own section. Kubectl get can retrieve information about all Kubernetes objects, as well as nodes in the Kubernetes data plane. The most common Kubernetes objects you are likely to query are pods, services, deployments, stateful sets, and secrets. List all pods in the default namespace in this case, there are no pods in the default namespace :. The NODE column shows on which node the pod is running or is scheduled. The kubernetes service is used to access the Kubernetes API from within the cluster and is usually located in the default namespace. Kubernetes stores secrets as baseencoded values, hence the base64 -d at the end to show a human-readable value. The base64 command is available on many operating systems, but you might need to change for your OS. There are many other commands to retrieve information besides kubectl get. In no particular order, here is a selection of the most important:. To retrieve a lot of information about Kubernetes objects that are not shown by kubectl get, use kubectl describe :. This command provides a lot of information and is very useful to understand why a pod is having problems. It shows the detailed status of all the containers, the mounted volumes, and the events associated with the pod. In most cases, running this command is all you need to understand why your pod is not working the way you want. If the problem is still not apparent, however, you might want to run kubectl describe node , which will provide you with useful information about the Kubernetes nodes, such as the cumulative allocated resources like CPU and memory. The -c argument is used to specify which container in the pod to query; if the pod has only one container, this argument is optional. Please note that kubectl logs will show the logs from the current log file on the node that is running the pod. Such log files are subject to rotation, so kubectl logs will show only the most recent log entries. Generally speaking, you would use kubectl logs only for debugging during the development stage. For production environments, you will most likely use a log aggregator and query for the logs from there. Nevertheless, this command is one of your first ports of call to troubleshoot misbehaving pods and connectivity problems. It should be noted that in many cases, you can get the logs of system pods running in the kube-system namespace, such as the API server, the DNS server, kube-proxy pods, etc. Some clusters have been set up to run those services directly on the control node s rather than pods, so in such cases you will need to check the logs directory on the control node s. These commands directly instruct Kubernetes to perform a specific operation on a given object. This section will show the most common such commands in no particular order. These are useful during the development stages, but you should definitely avoid them in a production environment. Use kubectl create to create a Kubernetes object, except for pods that are created using the kubectl run command. So to create a pod directly:. Using the run command is good enough for running simple pods. To delete the pod:. You can directly create all other Kubernetes objects using the kubectl create command. Here is a silly example for creating a Deployment:. Please note that not all elements of a Kubernetes object can be modified after it has been created. Another method to modify a Kubernetes object is to use the patch command. With the above deployment object, such a command could look like this:. This is one example where working with manifest files and using the declarative style make things much easier. You can also use the kubectl set command to easily modify certain objects, but it is limited in scope and not generic. It is mostly used to modify the image of pods or deployments, for example:. Another way to modify objects is to add or change the labels and annotations attached to it, for example:. When you want to work in declarative mode, you will have a manifest file or a set of them , and essentially use only one command:. Here, X is a file or a directory you can add multiple -f arguments if necessary. If you want to make some changes to your existing Kubernetes objects, just modify the manifest files and run kubectl apply again. This will compute the differences between your desired state and the existing state and make the necessary changes to reconcile them. If you use kustomization files, you should use the -k option instead, and the argument must be a directory:. There is a special case where the reconciliation is problematic, which has to do with the Kubernetes authorization system. The reasons for this are quite obscure and are touched on here if you are interested. If you make changes to RBAC resources or roles, you should use the kubectl auth reconcile command. You can find more information on this in the official Kubernetes documentation. Here are some useful commands to manage deployments in a general sense, so that also includes stateful sets and daemon sets. In practice, however, these commands are seldom used because you would manage deployments using Helm or some other similar software. Again, in practice, you are likely either to use Helm to perform static, manual changes or the pod autoscaler and not perform any manual operation. BTW, you can set up some basic autoscaling using kubectl autoscale , although that works only with one metric: CPU utilization. If your Docker registry is private, you will need to pass some credentials to Kubernetes. The easiest way to do this is to first login using the Docker command line, for example, on AWS:. So, if you see that error and you are using a private registry, you might want to check that you did set imagePullSecrets , and that the secret is not expired. Nothing beats getting a shell to a running pod! Consequently, you might need to think about how such containers will be troubleshooted. You might want to have two versions of such containers: One for development with the shell and maybe other programs and one for production which would be distroless. You can quickly create a link between a given port number on a given pod running inside the Kubernetes cluster and your computer this is called port forwarding. Here is how to do it, assuming your pod exposes port You can then open up port on your local computer and that will forward the traffic to the pod MYPOD on its port This is very useful to do a quick check on your pod to verify that it looks OK. You can copy files and directories using the kubectl cp command. It is useful to be able to complete your shell commands, and kubectl has a ready-made solution for that:. Kubectl supports a number of shells, and you will need to consult Kubernetes documentation for more details. Please note you will also need to install the bash-completion package for your Operating System if not already installed. Also, the above command will enable autocompletion only for the current session; to make it permanent, add this command to your shell initialization file. Finally, a very useful command to test your RBAC rules is kubectl auth can-i. Here is an example to test whether a given service account can read a certain config map:. You will obviously need to replace the capitalized placeholders with the names that make sense for your setup. Kubernetes is a complex system, and often, something will go wrong, simply because it can. This process, however, can often run out of hand and turn into a stressful, ineffective, and time-consuming task. This is the reason why we created Komodor, a tool that helps dev and ops teams stop wasting their precious time looking for needles in hay stacks every time things go wrong. If you are interested in checking out Komodor, use this link to sign up for a Free Trial. This website uses cookies. By continuing to browse, you agree to our Privacy Policy. Guides Kubernetes Troubleshooting. What is Kubectl If you are reading this article, you are probably familiar with Kubernetes and want to interact with a Kubernetes cluster. Kubectl offers three techniques. The command for this is kubectl apply -f manifest. Detect and fix errors 5x faster Komodor monitors your entire K8s stack, identifies issues, and uncovers their root cause. Kubectl Get Kubectl get is probably the command you will use the most, so it deserves its own section. Kubectl get offers a range of output formats: -o wide just adds more information which is dependent on the type of objects being queried. Other Commands to Get Information There are many other commands to retrieve information besides kubectl get. Imperative Commands These commands directly instruct Kubernetes to perform a specific operation on a given object. Managing Deployments Here are some useful commands to manage deployments in a general sense, so that also includes stateful sets and daemon sets. Interacting With Pods This section will list a bunch of commands that are very useful to interact with your pods. Kubernetes Troubleshooting With Komodor Kubernetes is a complex system, and often, something will go wrong, simply because it can. Acting as a single source of truth SSOT for all of your k8s troubleshooting needs, Komodor offers: Change intelligence : Every issue is a result of a change. Within seconds we can help you understand exactly who did what and when. In-depth visibility : A complete activity timeline, showing all code and config changes, deployments, alerts, code diffs, pod logs and etc. All within one pane of glass with easy drill-down options. Insights into service dependencies : An easy way to understand cross-service changes and visualize their ripple effects across your entire system. Seamless notifications : Direct integration with your existing communication channels e. Receive blog and product updates. Latest Articles.

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computingpostcom · 3 years ago

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Welcome to this exhilarating tutorial on how to deploy and use Quarkus in Kubernetes. Kubernetes is one of the open-source tools currently preferred when automating system deployments. It makes it easy to scale and manage containerized applications. Kubernetes works by distributing workloads across the cluster and automating the container networking needs. Also, storage and persistent volumes are allocated, by doing so the desired state of container applications is continuously maintained. Quarkus offers provides an easy way to automatically generate the Kubernetes resources based on some defaults and the user-provided configuration. This Kubernetes-native Java framework also provides an extension used to build and push container images to a registry before the application is deployed to the target. Another feature about Quarkus is that it enabled one to use the Kubernetes ConfigMap as a configuration source without mounting them on the pod. The cool features associated with Quarkus are: Community and Standards: It provides a cohesive and fun-to-use full-stack framework by leveraging a growing list of over fifty best-of-breed libraries that you love and use Container First: It offers amazingly fast boot time, incredibly low RSS memory (not just heap size!) offering near-instant scale-up and high density memory utilization in container orchestration platforms like Kubernetes Unifies imperative and reactive: It allows developers to combine both the familiar imperative code and the reactive style when developing applications. Kube-Native: The combination of Quarkus and Kubernetes provides an ideal environment for creating scalable, fast, and lightweight applications. It highly increases the developer productivity with tooling, pre-built integrations, application services e.t.c By following this guide to the end, you will learn how to: Use Quarkus Dekorate extension to automatically generate Kubernetes manifests based on the source code and configuration Build and push images to Docker registry with Jib extension Deploy an application on Kubernetes without any manually created YAML in one click Use Quarkus Kubernetes Config to inject configuration properties from ConfigMap Let’s dive in! Setup Pre-requisites For this guide, you will require: Quarkus CLI Apache Maven 3.8.1+ (Optional) Access to a Kubernetes cluster A Kubernetes cluster can be deployed with the aid of the guides below: Run Kubernetes on Debian with Minikube Deploy Kubernetes Cluster on Linux With k0s Install Kubernetes Cluster on Ubuntu using K3s Install Kubernetes Cluster on Rocky Linux 8 with Kubeadm & CRI-O Once the cluster is running, install kubectl curl -LO "https://storage.googleapis.com/kubernetes-release/release/$(curl -s https://storage.googleapis.com/kubernetes-release/release/stable.txt)/bin/linux/amd64/kubectl" chmod +x kubectl sudo mv kubectl /usr/local/bin Ensure that you can access the cluster. # For k0s export KUBECONFIG=/var/lib/k0s/pki/admin.conf 1. Install Quarkus CLI The Quarkus CLI can be installed on Linux, macOS, and Windows (using WSL or bash compatible shell-like Cygwin or MinGW) by running the below commands: curl -Ls https://sh.jbang.dev | bash -s - trust add https://repo1.maven.org/maven2/io/quarkus/quarkus-cli/ curl -Ls https://sh.jbang.dev | bash -s - app install --fresh --force quarkus@quarkusio You can install it on Windows systems using the Powershell: iex "& $(iwr https://ps.jbang.dev) trust add https://repo1.maven.org/maven2/io/quarkus/quarkus-cli/" iex "& $(iwr https://ps.jbang.dev) app install --fresh --force quarkus@quarkusio" Once installed, restart your shell. The Quarkus CLI can also be installed using SDKMAN as below: sdk install quarkus 2. Create a Project Use the Quarkus command-line interface (CLI) to create a new project. The below command adds resteasy-reactive, Jib, and kubernetes dependencies. quarkus create app quarkus-example --extension=resteasy-reactive,kubernetes,jib

cd quarkus-example Sample Output: After this, you will have several files generated, among these files is the pom.xml file bearing dependencies to the build file: ......... io.quarkus quarkus-resteasy-reactive io.quarkus quarkus-kubernetes io.quarkus quarkus-container-image-jib ...... The good thing with Quarkus is that it generates Deployment/StatefulSet resources that it use your registry_username/test-quarkus-app:tag as the container image of the Pod. The image here is controlled by the Jib extension and can be customized using the application.properties as shown: Open the file for editing: vim src/main/resources/application.properties Add the following lines replacing where required. quarkus.container-image.group=registry_username quarkus.container-image.name=tutorial-app quarkus.container-image.tag=latest quarkus.container-image.username=registry_username quarkus.container-image.password=Your_registry -Password If no registry has not been specified, the default, docker.io registry will be used. A detailed demonstration on specifying a registry has been captured elsewhere in this guide. 3. Build and Deploy your Application Jib is used to build optimized images for Java applications without a Docker daemon and no need for the mastery of deep docker practices. Dekorate is a Java library that makes it simple to generate and decorate Kubernetes manifests. It generates manifests based on the annotations, source code, and configuration variables. Now build and deploy your application using Quarkus CLI: quarkus build -Dquarkus.container-image.push=true Sample Output: After the build process, you will have two files named kubernetes.json and kubernetes.yml under the target/kubernetes/ directory. # ls target/kubernetes kubernetes.json kubernetes.yml Both files contain both the Kubernetes Deployment and Service. For example, the kubernetes.yml file looks like this: # cat target/kubernetes/kubernetes.yml --- apiVersion: v1 kind: Service metadata: annotations: app.quarkus.io/build-timestamp: 2022-07-09 - 10:55:08 +0000 labels: app.kubernetes.io/name: tutorial-app app.kubernetes.io/version: latest name: tutorial-app spec: ports: - name: http port: 80 targetPort: 8080 selector: app.kubernetes.io/name: tutorial-app app.kubernetes.io/version: latest type: LoadBalancer --- apiVersion: apps/v1 kind: Deployment metadata: annotations: app.quarkus.io/build-timestamp: 2022-07-09 - 10:55:08 +0000 labels: app.kubernetes.io/version: latest app.kubernetes.io/name: tutorial-app name: tutorial-app spec: replicas: 1 selector: matchLabels: app.kubernetes.io/version: latest app.kubernetes.io/name: tutorial-app template: metadata: annotations: app.quarkus.io/build-timestamp: 2022-07-09 - 10:55:08 +0000 labels: app.kubernetes.io/version: latest app.kubernetes.io/name: tutorial-app spec: containers: - env: - name: KUBERNETES_NAMESPACE valueFrom: fieldRef: fieldPath: metadata.namespace image: registry_username/tutorial-app:latest imagePullPolicy: Always name: tutorial-app ports: - containerPort: 8080 name: http protocol: TCP You will also have the image pushed to your registry. DockerHub for this example: It is possible to generate a StatefulSet resource instead of the default Deployment resource via the application.properties; quarkus.kubernetes.deployment-kind=StatefulSet Now deploy the application to your Kubernetes cluster using any of the two manifests. For example: kubectl apply -f target/kubernetes/kubernetes.yml Verify if the deployment is up: # kubectl get deploy NAME READY UP-TO-DATE AVAILABLE AGE tutorial-app 1/1 1 1 13s

# kubectl get pods NAME READY STATUS RESTARTS AGE tutorial-app-bc774dc8d-k494g 1/1 Running 0 19s Check if the service is running: # kubectl get svc NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE kubernetes ClusterIP 10.96.0.1 443/TCP 31m tutorial-app LoadBalancer 10.102.87.114 80:30400/TCP 4m53s Access the deployment using the provided port 30400. This can be done using a web browser with the URL http://IP_Address:30400/hello Or from the terminal as shown: $ curl 192.168.205.4:30400/hello Hello from RESTEasy Reactive This is the output of the file at src/main/java/org/acme/GreetingResource.java 4. Tuning the generated resources using application.properties Quarkus allows one to tune the generated manifest using the application.properties file. Through this file, several configurations can be made. These include: A. Namespace Quarkus allows one to run the application in a chosen namespace. It omits the namespace in the generated manifest rather than enforcing it in the default namespace. Therefore, you can run the application in the desired namespace say test using the command: kubectl apply -f target/kubernetes/kubernetes.yml -n=test Aside from specifying the namespace when running the Kubernetes command, you can still capture the namespace in the application.properties as shown: quarkus.kubernetes.namespace=mynamespace Replace mynamespace with the desired namespace for the application. B. Defining a Docker registry There are several other registries that can be defined. If left undefined, docker.io is used. If you want ot use another registry such as quay.io, then you need to specify it: quarkus.container-image.registry=my.docker-registry.net my.docker-registry.net is the registry you want to use. C. Environment variables There are several ways of defining variables on Kubernetes. These includes: key/value pairs import all values from a Secret or ConfigMap interpolate a single value identified by a given field in a Secret or ConfigMap interpolate a value from a field within the same resource Environment variables from key/value pairs To add environment variables from key/value pairs, use the below syntax: quarkus.kubernetes.env.vars.my-env-var=foobar This adds MY_ENV_VAR=foobar as an environment variable. my-env-var is converted to uppercase and the dashes are replaced with underscores to result in MY_ENV_VAR. Environment variables from Secret To add key/value pairs of Secret as environment variables, add the lines below to application.properties: quarkus.kubernetes.env.secrets=my-secret,my-other-secret This will result in the following in the container environment: envFrom: - secretRef: name: my-secret optional: false - secretRef: name: my-other-secret optional: false You can set the variable by extracting a value defined by keyName form the my-secret: quarkus.kubernetes.env.mapping.foo.from-secret=my-secret quarkus.kubernetes.env.mapping.foo.with-key=keyName Resulting into: - env: - name: FOO valueFrom: secretKeyRef: key: keyName name: my-secret optional: false Environment variables from ConfigMap Quarkus can be used to add key/value pairs from ConfigMap as environment variables. To achieve this, you need to add the lines below separating the ConfigMap to be used as a source by a comma. For example: quarkus.kubernetes.env.configmaps=my-config-map,another-config-map This will result into: envFrom: - configMapRef: name: my-config-map optional: false - configMapRef: name: another-config-map optional: false It is also possible to extract keyName field from the my-config-map by using: quarkus.kubernetes.env.mapping.foo.from-configmap=my-configmap quarkus.kubernetes.env.mapping.foo.with-key=keyName This will generate a manifest with the below lines:

- env: - name: FOO valueFrom: configMapRefKey: key: keyName name: my-configmap optional: false That is it! Closing Thoughts That summarizes this guide on how to deploy and use Quarkus in Kubernetes. I am sure that you are now in a position to generate the Kubernetes resources based on some defaults and the user-provided configuration using Quarkus. I hope this was valuable.

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