#AWSLambda

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19 hours ago

AWS Lambda expands response streaming support to all commercial AWS Regions AWS Lambda response streaming is now available in all commercial AWS Regions, bringing full regional parity for this capability. Customers in newly supported Regions can use the InvokeWithResponseStream API to progressively stream response payloads back to clients as data becomes available. Response streaming enables functions to send partial responses to clients incrementally rather than buffering the entire response before transmission. This reduces time-to-first-byte (TTFB) latency and is well suited for latency-sensitive workloads such as LLM-based applications as well as web and mobile applications where users benefit from seeing responses appear incrementally. Response streaming supports payloads up to a default maximum of 200 MB. With this expansion, customers in all commercial Regions can stream responses using the InvokeWithResponseStream API through a supported AWS SDK, or through Amazon API Gateway REST APIs with response streaming enabled. Response streaming supports Node.js managed runtimes as well as custom runtimes. Streaming responses incur an additional cost for network transfer of the response payload. You are billed based on the number of bytes generated and streamed out of your Lambda function over the first 6 MB. To get started with Lambda response streaming, visit the AWS Lambda documentation.

🆕 AWS Lambda now supports response streaming in all commercial regions, enabling incremental data transmission to reduce latency. Use InvokeWithResponseStream API for Node.js and custom runtimes. Streaming incurs network transfer costs. For details, see AWS Lambda documentation.

#AWS #AwsLambda

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AWS News(Unofficial)

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19 hours ago

AWS Lambda expands response streaming support to all commercial AWS Regions AWS Lambda response streaming is now available in all commercial AWS Regions, bringing full regional parity for this capability. Customers in newly supported Regions can use the InvokeWithResponseStream API to progressively stream response payloads back to clients as data becomes available. Response streaming enables functions to send partial responses to clients incrementally rather than buffering the entire response before transmission. This reduces time-to-first-byte (TTFB) latency and is well suited for latency-sensitive workloads such as LLM-based applications as well as web and mobile applications where users benefit from seeing responses appear incrementally. Response streaming supports payloads up to a default maximum of 200 MB. With this expansion, customers in all commercial Regions can stream responses using the InvokeWithResponseStream API through a supported AWS SDK, or through Amazon API Gateway REST APIs with response streaming enabled. Response streaming supports Node.js managed runtimes as well as custom runtimes. Streaming responses incur an additional cost for network transfer of the response payload. You are billed based on the number of bytes generated and streamed out of your Lambda function over the first 6 MB. To get started with Lambda response streaming, visit the https://docs.aws.amazon.com/lambda/latest/dg/configuration-response-streaming.html.

AWS Lambda expands response streaming support to all commercial AWS Regions

AWS Lambda response streaming is now available in all commercial AWS Regions, bringing full regional parity for this capability. Customers in newly supported Regions can use the InvokeWithResponseStrea...

#AWS #AwsLambda

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AWS Heroes Blog Posts

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1 day ago

Serverless applications on AWS with Lambda using Java 25, API Gateway and DynamoDB - Part 4 SnapStart + DynamoDB request priming Introduction In part 1, we introduced our sample application. In part 2, we measured the...

✍️ New blog post by Vadym Kazulkin

Serverless applications on AWS with Lambda using Java 25, API Gateway and DynamoDB - Part 4 SnapStart + DynamoDB request priming

#aws #java #serverless #awslambda

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AWS Heroes Blog Posts

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1 week ago

Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 3 Introducing Lambda SnapStart Introduction In part 1, we introduced our sample application. In part 2, we measured the...

✍️ New blog post by Vadym Kazulkin

Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 3 Introducing Lambda SnapStart

#aws #java #serverless #awslambda

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AWS News(Unofficial)

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1 week ago

AWS Weekly Roundup: AWS AI/ML Scholars program, Agent Plugin for AWS Serverless, and more (March 30, 2026) Last week, what excited me most was the launch of the 2026 AWS AI & ML Scholars program by Swami Sivasubramanian, VP of AWS Agentic AI, to provide free AI education to up to 100,000 learners worldwide. The program has two phases: a Challenge phase where you’ll learn foundational generative AI skills, followed by a […]

AWS Weekly Roundup: AWS AI/ML Scholars program, Agent Plugin for AWS Serverless, and more (March 30, 2026)

Last week, what excited me most was the launch of the 202...

#AWS #AmazonAurora #AmazonPolly #AmazonSagemakerStudio #Announcements #AwsLambda #Dsql #News #PostgresqlCompatible #WeekInReview

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EkasCloud – Personalized Training Platform

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1 week ago

How Serverless Computing Is Changing Software Development The world of software development is undergoing a major transformation. As businesses demand faster innovation, scalable systems, and cost-efficient infrastructure, traditional development models...

How Serverless Computing Is Changing Software Development
www.ekascloud.com/our-blog/how...
#Serverless #ServerlessComputing #CloudComputing #AWSLambda #AzureFunctions #GoogleCloud #CloudNative #DevOps #Microservices #BackendDevelopment
#SoftwareDevelopment #Programming #Developers

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1 week ago

AWS Lambda supports up to 32 GB of memory and 16 vCPUs for Lambda Managed Instances AWS Lambda now supports up to 32 GB of memory and 16 vCPUs for functions running on Lambda Managed Instances, enabling customers to run compute-intensive workloads such as large-scale data processing, media transcoding, and scientific simulations without managing any infrastructure. Customers can also configure the memory-to-vCPU ratio — 2:1, 4:1, or 8:1 — to match the resource profile of their workload. Lambda Managed Instances lets you run Lambda functions on managed Amazon EC2 instances with built-in routing, load balancing, and auto-scaling, giving you access to specialized compute configurations including the latest-generation processors and high-bandwidth networking, with no operational overhead. Customers building compute-intensive applications such as data processing pipelines, high-throughput API backends, and batch computation workloads require substantial memory and CPU resources to process large datasets, serve low-latency responses at scale, and run complex computations efficiently. Previously, function execution environments on Lambda Managed Instances were limited to 10 GB of memory and approximately 6 vCPUs, with no option to customize the memory-to-vCPU ratio. Functions on Lambda Managed Instances can now be configured with up to 32 GB of memory, and a choice of memory-to-vCPU ratio — 2:1, 4:1, or 8:1 — allowing customers to select the right balance of memory and compute for their workload. For example, at 32 GB of memory, customers can configure 16 vCPUs (2:1), 8 vCPUs (4:1), or 4 vCPUs (8:1) depending on whether their workload is CPU-intensive or memory-intensive. This feature is available in all AWS Regions where Lambda Managed Instances is generally available. You can configure these settings using the AWS Console, AWS CLI, AWS CloudFormation, AWS CDK, or AWS SAM. To learn more, visit the AWS Lambda Managed Instances product page and documentation.

🆕 AWS Lambda now supports up to 32 GB memory and 16 vCPUs for Managed Instances, ideal for compute-intensive workloads. Customers can choose memory-to-vCPU ratios (2:1, 4:1, 8:1) for optimal resource allocation. Available in all regions with Lambda Managed Instances.

#AWS #AwsLambda

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AWS News(Unofficial)

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1 week ago

AWS Lambda supports up to 32 GB of memory and 16 vCPUs for Lambda Managed Instances AWS Lambda now supports up to 32 GB of memory and 16 vCPUs for functions running on Lambda Managed Instances, enabling customers to run compute-intensive workloads such as large-scale data processing, media transcoding, and scientific simulations without managing any infrastructure. Customers can also configure the memory-to-vCPU ratio — 2:1, 4:1, or 8:1 — to match the resource profile of their workload. Lambda Managed Instances lets you run Lambda functions on managed Amazon EC2 instances with built-in routing, load balancing, and auto-scaling, giving you access to specialized compute configurations including the latest-generation processors and high-bandwidth networking, with no operational overhead. Customers building compute-intensive applications such as data processing pipelines, high-throughput API backends, and batch computation workloads require substantial memory and CPU resources to process large datasets, serve low-latency responses at scale, and run complex computations efficiently. Previously, function execution environments on Lambda Managed Instances were limited to 10 GB of memory and approximately 6 vCPUs, with no option to customize the memory-to-vCPU ratio. Functions on Lambda Managed Instances can now be configured with up to 32 GB of memory, and a choice of memory-to-vCPU ratio — 2:1, 4:1, or 8:1 — allowing customers to select the right balance of memory and compute for their workload. For example, at 32 GB of memory, customers can configure 16 vCPUs (2:1), 8 vCPUs (4:1), or 4 vCPUs (8:1) depending on whether their workload is CPU-intensive or memory-intensive. This feature is available in all AWS Regions where Lambda Managed Instances is generally available. You can configure these settings using the AWS Console, AWS CLI, AWS CloudFormation, AWS CDK, or AWS SAM. To learn more, visit the https://aws.amazon.com/lambda/lambda-managed-instances/ and https://docs.aws.amazon.com/lambda/latest/dg/lambda-managed-instances.html.

AWS Lambda supports up to 32 GB of memory and 16 vCPUs for Lambda Managed Instances

AWS Lambda now supports up to 32 GB of memory and 16 vCPUs for functions running on Lambda Managed Instances, enabling customers to run compute-intensive workloads such as large-scale data proc...

#AWS #AwsLambda

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AWS Heroes Blog Posts

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2 weeks ago

Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 2 Initial performance measurements Introduction In part 1, we introduced our 2 sample applications (one using JDBC directly...

✍️ New blog post by Vadym Kazulkin

Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 2 Initial performance measurements

#aws #java #serverless #awslambda

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AWS News(Unofficial)

@awsnews.bsky.social

2 weeks ago

AWS Weekly Roundup: NVIDIA Nemotron 3 Super on Amazon Bedrock, Nova Forge SDK, Amazon Corretto 26, and more (March 23, 2026) Hello! I’m Daniel Abib, and this is my first AWS Weekly Roundup. I’m a Senior Specialist Solutions Architect at AWS, focused on the generative AI and Amazon Bedrock. With over 28 years of experience in solution architecture, software development, and cloud architecture, I help Startups & Enterprises harness the power of generative AI with Amazon […]

AWS Weekly Roundup: NVIDIA Nemotron 3 Super on Amazon Bedrock, Nova Forge SDK, Amazon Corretto 26, and more (March 23, 2026)

Hello! I’m Daniel Abib,...

#AWS #AmazonBedrockAgentcore #AmazonCloudwatch #AmazonConnect #AmazonCorretto #AmazonNova #AmazonRedshift #AwsLambda #Kiro #News #WeekInReview

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AWS Heroes Blog Posts

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2 weeks ago

Serverless applications on AWS using Lambda with Java 25, API Gateway and DynamoDB - Part 2 Initial performance measurements Introduction In part 1 of the series, we introduced our sample application. In this...

✍️ New blog post by Vadym Kazulkin

Serverless applications on AWS using Lambda with Java 25, API Gateway and DynamoDB - Part 2 Initial performance measurements

#aws #java #serverless #awslambda

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AWS News Feed on 🦋

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2 weeks ago

AWS Lambda now supports Availability Zone metadata AWS Lambda now provides Availability Zone (AZ) metadata through a new metadata endpoint in the Lambda execution environment. With this capability, developers can determine the AZ ID (e.g., use1-az1) of the AZ their Lambda function is running in, enabling them to build functions that make AZ-aware routing decisions, such as preferring same-AZ endpoints for downstream services to reduce cross-AZ latency. This capability also enables operators to implement AZ-aware resilience patterns like AZ-specific fault injection testing. Lambda automatically provisions and maintains execution environments ready to serve function invocations across multiple AZs within an AWS Region to provide high availability and fault tolerance without any additional configuration or management overhead for customers. As development teams scale their serverless applications, their functions often need to interact with other AWS services like Amazon ElastiCache and Amazon RDS that provide endpoints specific to each AZ. Until now, Lambda did not provide a way for functions to determine which AZ they were running in. With the new metadata endpoint, functions can now retrieve their AZ ID with a simple HTTP request, making it easy to implement AZ-aware logic without building and maintaining custom solutions. To get started, use the Powertools for AWS Lambda metadata utility or call the metadata endpoint directly using the environment variables that Lambda automatically sets in the execution environment. This capability is supported for all Lambda runtimes, including custom runtimes and functions packaged as container images, and integrates seamlessly with Lambda capabilities like SnapStart and provisioned concurrency, regardless of whether your functions are VPC-enabled.  AZ metadata support is available at no additional cost in all commercial AWS Regions where Lambda is available. To learn more, visit Lambda documentation.

🆕 AWS Lambda now offers Availability Zone metadata via a new endpoint, enabling developers to determine the AZ ID of their function's runtime, aiding in AZ-aware routing and resilience patterns, at no extra cost in all commercial regions. Use Powertools or direct HTTP requests.

#AWS #AwsLambda

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AWS News(Unofficial)

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2 weeks ago

AWS Lambda now supports Availability Zone metadata AWS Lambda now provides Availability Zone (AZ) metadata through a new metadata endpoint in the Lambda execution environment. With this capability, developers can determine the AZ ID (e.g., use1-az1) of the AZ their Lambda function is running in, enabling them to build functions that make AZ-aware routing decisions, such as preferring same-AZ endpoints for downstream services to reduce cross-AZ latency. This capability also enables operators to implement AZ-aware resilience patterns like AZ-specific fault injection testing. Lambda automatically provisions and maintains execution environments ready to serve function invocations across multiple AZs within an AWS Region to provide high availability and fault tolerance without any additional configuration or management overhead for customers. As development teams scale their serverless applications, their functions often need to interact with other AWS services like Amazon ElastiCache and Amazon RDS that provide endpoints specific to each AZ. Until now, Lambda did not provide a way for functions to determine which AZ they were running in. With the new metadata endpoint, functions can now retrieve their AZ ID with a simple HTTP request, making it easy to implement AZ-aware logic without building and maintaining custom solutions. To get started, use the https://docs.aws.amazon.com/powertools/typescript/latest/  metadata utility or call the metadata endpoint directly using the environment variables that Lambda automatically sets in the execution environment. This capability is supported for all Lambda runtimes, including custom runtimes and functions packaged as container images, and integrates seamlessly with Lambda capabilities like SnapStart and provisioned concurrency, regardless of whether your functions are VPC-enabled.  AZ metadata support is available at no additional cost in all commercial https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/ where Lambda is available. To learn more, visit https://docs.aws.amazon.com/lambda/latest/dg/configuration-metadata-endpoint.html.

AWS Lambda now supports Availability Zone metadata

AWS Lambda now provides Availability Zone (AZ) metadata through a new metadata endpoint in the Lambda execution environment. With this capability, developers can determine the AZ ID (e.g., use1-az1) of the AZ their Lambda ...

#AWS #AwsLambda

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AWS Heroes Blog Posts

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3 weeks ago

Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 1 Sample applications Introduction In this article series, we'll explain how to implement a serverless...

✍️ New blog post by Vadym Kazulkin

Serverless applications on AWS with Lambda using Java 25, API Gateway and Aurora DSQL - Part 1 Sample applications

#aws #java #serverless #awslambda

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AWS Heroes Blog Posts

@awsheroesblogposts.bsky.social

3 weeks ago

Serverless applications on AWS using Lambda with Java 25, API Gateway and DynamoDB - Part 1 Sample application Introduction In this article series, we'll explain how to implement a serverless...

✍️ New blog post by Vadym Kazulkin

Serverless applications on AWS using Lambda with Java 25, API Gateway and DynamoDB - Part 1 Sample application

#aws #java #serverless #awslambda

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AWS Community Builder Blog Posts

@awscmblogposts.bsky.social

3 weeks ago

MCP Development with Amazon Lambda and Gemini CLI Leveraging Gemini CLI and the underlying Gemini LLM to build Model Context Protocol (MCP) AI...

✍️ New blog post by xbill

MCP Development with Amazon Lambda and Gemini CLI

#python #gemini #awslambda #mcpserver

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AWS News Feed on 🦋

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3 weeks ago

🆕 AWS Lambda Managed Instances now support Rust, offering high-performance functions with Lambda’s simplicity, specialized compute, and EC2 pricing. Available in all regions. See Lambda docs to start.

#AWS #AwsLambda

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AWS News(Unofficial)

@awsnews.bsky.social

3 weeks ago

AWS Lambda Managed Instances now supports Rust

AWS Lambda Managed Instances now supports Rust, enabling developers to run high-performance Rust-based functions on Lambda-managed Amazon EC2 instances while maintaining Lambda’s operational simplicity. This combination makes it...

#AWS #AwsLambda

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International PHP Conference 2026

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4 weeks ago

☁️ #Serverless #PHP in the real world

Carsten Windler shares what teams should know before running PHP with bref.sh on #AWSLambda — from cold starts to architecture trade-offs.

#IntPHPCon |📍BER | 📅 June 8 – 12, 26

▶️ More about the session: https://f.mtr.cool/mtvkmmhgey

#DevOps #Bref

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AWS News Feed on 🦋

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1 month ago

Accelerate Lambda durable functions development with new Kiro power Today, AWS announces the Lambda durable functions Kiro power, bringing Lambda durable function development expertise to agentic AI development in Kiro. With this power, you can build resilient, long-running multi-step applications and AI workflows faster with AI agent-assisted development directly in your local development environment. When you work with durable functions, the AI agent dynamically loads relevant guidance and development expertise. This includes replay model best practices, step and wait operations, concurrent execution with map and parallel patterns, error handling with retry strategies and compensating transactions, testing patterns, and deployment with AWS CloudFormation, AWS Cloud Development Kit (AWS CDK), and AWS Serverless Application Model (AWS SAM). With this guidance, you can go from idea to a working durable function quickly, whether you are building order processing pipelines, AI agent orchestration with human-in-the-loop approvals, or payment coordination workflows. The Lambda durable functions power is available today with one-click installation from the Kiro IDE and the Kiro powers page. Explore the power on GitHub. To get started with Lambda durable functions, see the developer guide.

🆕 AWS introduces Kiro power for Lambda durable functions, enabling faster development of resilient, long-running applications with AI agent-assisted guidance on best practices, error handling, and deployment tools. Available via one-click in Kiro IDE.

#AWS #AwsLambda

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AWS News(Unofficial)

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1 month ago

Accelerate Lambda durable functions development with new Kiro power Today, AWS announces the Lambda durable functions Kiro power, bringing Lambda durable function development expertise to agentic AI development in Kiro. With this power, you can build resilient, long-running multi-step applications and AI workflows faster with AI agent-assisted development directly in your local development environment. When you work with durable functions, the AI agent dynamically loads relevant guidance and development expertise. This includes replay model best practices, step and wait operations, concurrent execution with map and parallel patterns, error handling with retry strategies and compensating transactions, testing patterns, and deployment with AWS CloudFormation, AWS Cloud Development Kit (AWS CDK), and AWS Serverless Application Model (AWS SAM). With this guidance, you can go from idea to a working durable function quickly, whether you are building order processing pipelines, AI agent orchestration with human-in-the-loop approvals, or payment coordination workflows. The Lambda durable functions power is available today with one-click installation from the https://kiro.dev/launch/powers/aws-lambda-durable-functions/ and the https://kiro.dev/powers/. Explore the https://github.com/aws/aws-durable-execution-docs/tree/main/aws-lambda-durable-functions-power. To get started with Lambda durable functions, see the https://docs.aws.amazon.com/lambda/latest/dg/durable-functions.html.

Accelerate Lambda durable functions development with new Kiro power

Today, AWS announces the Lambda durable functions Kiro power, bringing Lambda durable function development expertise to agentic AI development in Kiro. With this power, you can build resilient, long-running mu...

#AWS #AwsLambda

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AWS News Feed on 🦋

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1 month ago

AWS Lambda Durable Execution SDK for Java now available in Developer Preview Today, AWS announces the developer preview of the AWS Lambda Durable Execution SDK for Java. With this SDK, developers can build resilient multi-step applications like order processing pipelines, AI-assisted workflows, and human-in-the-loop approvals using Lambda durable functions, without implementing custom progress tracking or integrating external orchestration services. Lambda durable functions extend Lambda's event-driven programming model with operations that checkpoint progress automatically and pause execution for up to a year when waiting on external events. The new Durable Execution SDK for Java provides an idiomatic experience for building with durable functions and is compatible with Java 17+. This preview includes steps for progress tracking, waits for efficient suspension, and durable futures for callback-based workflows. To get started, see the Lambda durable functions developer guide and the AWS Lambda Durable Execution SDK for Java on GitHub. To learn more about Lambda durable functions, visit the product page. On-demand functions are not billed for duration while paused. For pricing details, see AWS Lambda Pricing. For information about AWS Regions where Lambda durable functions are available, see the AWS Regional Services List.

🆕 AWS releases a Java Lambda Durable Execution SDK preview for resilient multi-step apps, like order pipelines, with automatic checkpoints and pausing up to a year. Java 17+ compatible, no external services required. For more, check the Lambda guide and GitHub.

#AWS #AwsLambda

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AWS News(Unofficial)

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1 month ago

AWS Lambda Durable Execution SDK for Java now available in Developer Preview Today, AWS announces the developer preview of the AWS Lambda Durable Execution SDK for Java. With this SDK, developers can build resilient multi-step applications like order processing pipelines, AI-assisted workflows, and human-in-the-loop approvals using Lambda durable functions, without implementing custom progress tracking or integrating external orchestration services. Lambda durable functions extend Lambda's event-driven programming model with operations that checkpoint progress automatically and pause execution for up to a year when waiting on external events. The new Durable Execution SDK for Java provides an idiomatic experience for building with durable functions and is compatible with Java 17+. This preview includes steps for progress tracking, waits for efficient suspension, and durable futures for callback-based workflows. To get started, see the https://docs.aws.amazon.com/lambda/latest/dg/durable-functions.html and the https://github.com/aws/aws-durable-execution-sdk-java/. To learn more about Lambda durable functions, visit the https://aws.amazon.com/lambda/lambda-durable-functions/. On-demand functions are not billed for duration while paused. For pricing details, see https://aws.amazon.com/lambda/pricing/. For information about AWS Regions where Lambda durable functions are available, see the https://builder.aws.com/build/capabilities.

AWS Lambda Durable Execution SDK for Java now available in Developer Preview

Today, AWS announces the developer preview of the AWS Lambda Durable Execution SDK for Java. With this SDK, developers can build resilient multi-step applications like order processing pipelines, AI-a...

#AWS #AwsLambda

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Airon

@airon-tark.bsky.social

1 month ago

Tark Labs routine #89: Firebase added phone verification. Nice move! AWS has it for years 😄 #firebase #aws #awsamplify #awslambda #awscognito #awsdynamodb #appdev #mobiledev #tarklabs #airontark

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Steef-Jan Wiggers

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1 month ago

AWS Enables Lambda Function Triggers from RDS for SQL Server Database Events In a blog post, AWS recently described an event-driven pattern for Amazon RDS for SQL Server, allowing developers to trigger Lambda functions in response to database events via CloudWatch Logs and SQS...

AWS recently described an event-driven pattern for Amazon RDS for SQL Server, allowing developers to trigger Lambda functions in response to database events via CloudWatch Logs and SQS in a blog post. #amazon #rds #eventdriven #aws #faas #infoq #awslambda #serverless www.infoq.com/news/2026/02...

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AWS News(Unofficial)

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2 months ago

Build multi-step applications and AI workflows with AWS Lambda durable functions New Lambda capability lets you build applications that coordinate multiple steps reliably over extended periods—from seconds to up to one year—without paying for idle compute time when waiting for external events or human decisions.

Build multi-step applications and AI workflows with AWS Lambda durable functions

New Lambda capability lets you build applications that coordinate multiple steps reliably over extended periods—from seconds to up to one year—without paying for idle co...

#AWS #AwsLambda #Compute #Launch #News

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AntStack

@antstack.com

2 months ago

AWS re:Invent 2025 changed Lambda, and most teams haven’t caught up.

Akshatha Laxmi breaks down Lambda Managed Instances: EC2-backed execution, fewer cold starts, and better performance for high-throughput workloads.

👉 Watch: antt.me/0jNiTXIv

#AWSLambda #AntStackTV

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InfoQ

@infoq.com

2 months ago

From a Lambda-Lith to an Event Driven Architecture – Lessons Learned Leo Hanisch discusses the challenges of the "Lambda-Lith" approach and the benefits of embracing EDAs.

4/5 ➡️ From a Lambda-Lith to an Event Driven Architecture - Lessons Learned by Leo Hanisch
bit.ly/3RchqJJ

#AWSLambda

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Elizabeth Fuentes L

@elizabethfue12.bsky.social

2 months ago

Is this code deterministic? I recently posted a small code snippet in a LinkedIn poll and asked what sounded like a simple...

🚀📝 Is this code deterministic?

#deterministic #durableexecution #AWSLambda #idempotent #replaySafe

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AWS News(Unofficial)

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2 months ago

AWS Lambda announces cross-account access for DynamoDB Streams AWS Lambda now supports cross-account access for AWS DynamoDB Streams event-source mappings (ESMs), enabling you to trigger Lambda functions in one account from DynamoDB Streams in another account. Customers build event-driven applications using Lambda's fully-managed DynamoDB Streams ESMs, which poll change events from DynamoDB tables and trigger your Lambda functions. Organizations implementing multi-account architectures—whether to centralize event processing or share events with partner teams—previously needed to build complex data replication solutions to share data across accounts, which added operational overhead . With this launch, you can now provide cross-account access to your DynamoDB Streams to trigger Lambda functions in another account. By setting a https://docs.aws.amazon.com/amazondynamodb/latest/developerguide/access-control-resource-based.html on your DynomoDB stream, you can enable a Lambda function in one account to access DynomoDB stream in another account. This capability allows you to simplify your streaming applications across accounts without the overhead of replication solutions in each account. This feature is generally available in all https://aws.amazon.com/about-aws/global-infrastructure/regional-product-services/. You can enable cross-account Lambda triggers by creating resource-based policies for your DynamoDB Streams using the AWS Management Console, AWS CLI, AWS SDKs, AWS CloudFormation, or AWS APIs. To learn more, read Lambda ESM https://docs.aws.amazon.com/lambda/latest/dg/services-dynamodb-eventsourcemapping.html#services-dynamodb-eventsourcemapping-cross-accounthttps://docs.aws.amazon.com/lambda/latest/dg/invocation-eventsourcemapping.html#invocation-eventsourcemapping-provisioned-mode

AWS Lambda announces cross-account access for DynamoDB Streams

AWS Lambda now supports cross-account access for AWS DynamoDB Streams event-source mappings (ESMs),
enabling you to trigger Lambda functions in one account from DynamoDB Streams in another account....

#AWS #AwsLambda #AwsGovcloudUs

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Posts tagged #AWSLambda