article thumbnail

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.

article thumbnail

AWS EKS Monitoring as a Self-Service with Dynatrace

Dynatrace

PostgreSQL & Elastic for data storage. 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. NGINX as an API Gateway.

AWS 128
Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

Trending Sources

article thumbnail

AWS serverless services: Exploring your options

Dynatrace

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Speed is next; serverless solutions are quick to spin up or down as needed, and there are no delays due to limited storage or resource access. AWS offers four serverless offerings for storage.

article thumbnail

In-Stream Big Data Processing

Highly Scalable

The pipelines can be stateful and the engine’s middleware should provide a persistent storage to enable state checkpointing. 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. Marz, “Big Data Lambda Architecture”. Jacobsen and R.

Big Data 154
article thumbnail

Cloudburst: stateful functions-as-a-service

The Morning Paper

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

Lambda 98
article thumbnail

How to Reduce Your CDN Infrastructure Expenses

IO River

For example, Lambda@Edge request pricing is $0.6 Capacity CommitmentCommitting to a certain capacity for CDNs saves money by giving you a discounted rate on CDN bandwidth and storage. For example, the first 10TB to South America cost $0.11.Source: per one million requests. Origin Shield costs $0.009 for 10,000 requests to Singapore.‍Source:

article thumbnail

How to Reduce Your CDN Infrastructure Expenses

IO River

For example, Lambda@Edge request pricing is $0.6 Capacity CommitmentCommitting to a certain capacity for CDNs saves money by giving you a discounted rate on CDN bandwidth and storage. For example, the first 10TB to South America cost $0.11.Source: per one million requests.