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Dynatrace supports SnapStart for Lambda as an AWS launch partner

Dynatrace

Dynatrace is proud to be an AWS launch partner in support of Amazon Lambda SnapStart. For AWS Lambda, the largest contributor to startup latency is the time spent initializing an execution environment, which includes loading function code and initializing dependencies. What is Lambda? What is Lambda SnapStart?

Lambda 225
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Choosing a cloud DBMS: architectures and tradeoffs

The Morning Paper

Which I’m quite happy to see as my most recent data pipeline is based around Lambda, S3, and Athena, and it’s been working great for my use case. For query executors that can be frequently started and stopped the authors explore performance with cold and warm caches (where applicable), and also the horizontal and vertical scaling performance.

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AWS serverless services: Exploring your options

Dynatrace

Scalability. Finally, there’s scalability. Lambda functions can be written in the language of your choice, and the service also supports container tools. Amazon EventBridge: EventBridge to bridges the data gap between your applications and other services, such as Lambda or specific SaaS apps. Data Store.

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Embrace event-driven computing: Amazon expands DynamoDB with streams, cross-region replication, and database triggers

All Things Distributed

Streams provide you with the underlying infrastructure to create new applications, such as continuously updated free-text search indexes, caches, or other creative extensions requiring up-to-date table changes. An AWS Lambda function is a simpler option that you can use, as it only requires you to code the logic, set it, and forget it.

Database 167
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In-Stream Big Data Processing

Highly Scalable

In many cases join is performed on a finite time window or other type of buffer e.g. LFU cache that contains most frequent tuples in the stream. Kafka messaging queue is well known implementation of such a buffer that also supports scalable distributed deployments, fault-tolerance, and provides high performance. Jacobsen and R.

Big Data 154
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Accelerating Data: Faster and More Scalable ElastiCache for Redis

All Things Distributed

Since then we’ve introduced Amazon Kinesis for real-time streaming data, AWS Lambda for serverless processing, Apache Spark analytics on EMR, and Amazon QuickSight for high performance Business Intelligence. Amazon’s enhancements address many day-to-day challenges with running Redis.

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Content Management Systems of the Future: Headless, JAMstack, ADN and Functions at the Edge

Abhishek Tiwari

In addition, traditional CMS solutions lack integration with modern software stack, cloud services, and software delivery pipelines. Using JAMstack delivers better performance, higher scalability with less cost, and overall a better developer experience as well as user experience. At the core, a traditional CMS is a monolith.

Systems 63