Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. It became clear that real-time query processing and in-stream processing is the immediate need in many practical applications. Fault-tolerance.

Big Data 154

Big Data Processing Lambda Database 154

Adrian Cockcroft

JANUARY 29, 2023

> system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, > system.time(wait1 <- normalmixEM(waiting, mu=c(50,80), lambda=.5, The normal fitted peaks are then subtracted out of the data.

Lambda 98

Lambda Latency Cache C++ 98

Dynatrace

SEPTEMBER 17, 2019

REDIS for caching. In order to filter these dashboards by tenant all they need is a Dynatrace Management Zone , which is based on meta data extracted by Dynatrace from e.g. k8s tags, container labels or process environment variables. Their technology stack looks like this: Spring Boot-based Microservices. NGINX as an API Gateway.

AWS 128

AWS Monitoring Ecommerce Lambda 128

Dynatrace

OCTOBER 7, 2021

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Lambda functions can be written in the language of your choice, and the service also supports container tools. AWS Step Functions: Step Functions focuses on orchestration. Data Store.

Serverless 285

Serverless AWS Lambda Storage 285

The Morning Paper

AUGUST 29, 2019

My key takeaways as a TL;DR: Store your data in S3 Use portable data format that gives you future flexibility to process it with multiple different systems (e.g. 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.

Architecture 76

Architecture Cloud Storage Serverless 76

The Morning Paper

FEBRUARY 6, 2020

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).

Serverless 98

Serverless Lambda Cache Latency 98

All Things Distributed

JUNE 21, 2018

A common question that I get is why do we offer so many database products? To do this, they need to be able to use multiple databases and data models within the same application. Seldom can one database fit the needs of multiple distinct use cases. Seldom can one database fit the needs of multiple distinct use cases.

Database 167

Database AWS Games Latency 167