Remove Analytics Remove Cache Remove Lambda Remove Scalability
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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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AWS EKS Monitoring as a Self-Service with Dynatrace

Dynatrace

Cluster and container Log Analytics. REDIS for caching. With the existing notification integrations for tools such as Slack, xMatters, ServiceNow, Lambda, JIRA, you can also pro-actively notify people in case there’s a problem: Dynatrace auto detected a problem with 3 kube proxies. 3 Log Analytics. Service mash insights.

AWS 127
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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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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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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. Building upon Redis. Amazon’s enhancements address many day-to-day challenges with running Redis.

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A one size fits all database doesn't fit anyone

All Things Distributed

As I have talked about before, one of the reasons why we built Amazon DynamoDB was that Amazon was pushing the limits of what was a leading commercial database at the time and we were unable to sustain the availability, scalability, and performance needs that our growing Amazon.com business demanded. The opposite is true.

Database 167
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Content Management Systems of the Future: Headless, JAMstack, ADN and Functions at the Edge

Abhishek Tiwari

Most of the CMS vendors dodge questions of evolution by talking about incremental innovation primarily focused on customer experience (CX) such as analytics and personalisation. Using JAMstack delivers better performance, higher scalability with less cost, and overall a better developer experience as well as user experience.

Systems 63