Abhishek Tiwari

JULY 12, 2018

Data Pipeline A data pipeline is a software that ingests data from multiple sources, transforms it and finally makes it available to internal or external products. A data pipeline is a software which runs on hardware. The software is error-prone and hardware failures are inevitable.

Latency 63

Latency Analytics Scalability Engineering 63

Dynatrace

JANUARY 26, 2021

This allows teams to sidestep much of the cost and time associated with managing hardware, platforms, and operating systems on-premises, while also gaining the flexibility to scale rapidly and efficiently. In a serverless architecture, applications are distributed to meet demand and scale requirements efficiently.

Serverless 243

Serverless Efficiency Lambda Azure 243

Dynatrace

MAY 1, 2020

Other distributions like Debian and Fedora are available as well, in addition to other software like VMware, NGINX, Docker, and, of course, Java. We anticipate massive growth in the popularity of this architecture in the coming quarters, driven additionally by companies’ push for cost reductions. Stay tuned for more details.

Java 133

Java Hardware Tuning Metrics 133

Dynatrace

AUGUST 12, 2020

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. Dynatrace is thrilled to announce the General Availability of support for both the 2.x It allows for the breaking up of heavy monolithic architectures into multiple serverless “functions.” So stay tuned!

Serverless 236

Serverless Azure Monitoring Lambda 236

Dynatrace

NOVEMBER 15, 2021

Log monitoring, log analysis, and log analytics are more important than ever as organizations adopt more cloud-native technologies, containers, and microservices-based architectures. Logs can include data about user inputs, system processes, and hardware states. Dynatrace news. billion in 2020 to $4.1 What are logs?

Analytics 208

Analytics Monitoring Artificial Intelligence DevOps 208

Dynatrace

AUGUST 12, 2020

As companies strive to innovate and deliver faster, modern software architecture is evolving at near the speed of light. Dynatrace is thrilled to announce the General Availability of support for both the 2.x It allows for the breaking up of heavy monolithic architectures into multiple serverless “functions.” So stay tuned!

Serverless 141

Serverless Azure Monitoring Lambda 141

Dynatrace

NOVEMBER 20, 2019

Having released this functionality in an Early Adopter Release with OneAgent version 1.173 and Dynatrace version 1.174 back in August 2019, we’re now happy to announce the General Availability of OneAgent full-stack monitoring for Linux on the IBM Z platform, sometimes informally referred to as Z/Linux. Host-performance measures.

Availability 31

Availability Hardware Java Tuning 31

All Things Distributed

OCTOBER 8, 2014

We designed DynamoDB to operate with at least 99.999% availability. We started with Amazon Dynamo, a simple key-value store that was built to be highly available and scalable to power various mission-critical applications in Amazon’s e-commerce platform. In 2012, we launched Amazon DynamoDB, the successor to Amazon Dynamo.

Availability 145

Availability Performance Scalability AWS 145

Dynatrace

AUGUST 8, 2019

We’re happy to announce the Early Adopter Release of OneAgent full-stack monitoring for Linux on the IBM Z platform, sometimes informally referred to as Z/Linux (available with OneAgent version 1.173 and Dynatrace version 1.174). For details on available metrics, see our help page on host performance monitoring.

Availability 25

Availability Hardware Java Tuning 25

Percona

APRIL 17, 2023

The main objective of this post is to share my experience over the past years tuning MongoDB and centralize the diverse sources that I crossed in this journey in a unique place. There is an issue with this, which causes the OS to swap even with memory available. Spoiler alert: This post focuses on MongoDB 3.6.X 25.84 - Total 21.04

Best Practices 52

Best Practices Design Tuning Database 52

SQL Performance

APRIL 27, 2020

Gen 5 is the primary hardware option now for most regions since Gen 4 is aging out. I highly recommend that you take a look at the diagram that breaks down the architecture and how it all works in this article. New Hardware Configuration for Provisioned Compute Tier. GB per vCore. Serverless Database. Conclusion.

Azure 55

Azure Database Serverless Hardware 55

All Things Distributed

MARCH 7, 2013

As I sat down with the DynamoDB team to review our progress over the last year, I realized that DynamoDB had surpassed even my own expectations for how easily applications could achieve massive scale and high availability with DynamoDB. This rapid adoption has allowed us to benefit from the scale economies inherent in our architecture.

Ecommerce 139

Ecommerce Storage Scalability Hardware 139

The Morning Paper

NOVEMBER 10, 2019

Rather than reimplement TCP/IP or refactor an existing transport, we started Pony Express from scratch to innovate on more efficient interfaces, architecture, and protocol. The ability to rapidly deploy new versions of Pony Express significantly aided development and tuning of congestion control. Emphasis mine).

Network 92

Network Transportation Latency Entertainment 92

Dynatrace

OCTOBER 22, 2019

A scalable architecture needs to distribute work across many threads in order to facilitate all the CPUs of a physical or virtual machine. Locking is the Achilles heel of any multi-threaded architecture. Ultimately, it leads to a state where your system won’t be able to process more data even if you add more hardware.

Java 103

Java Scalability Hardware Architecture 103

HammerDB

JANUARY 5, 2019

Some opinions claim that “Benchmarks are meaningless”, “benchmarks are irrelevant” or “benchmarks are nothing like your real applications” However for others “Benchmarks matter,” as they “account for the processing architecture and speed, memory, storage subsystems and the database engine.”

Benchmarking 40

Benchmarking Database Social Media Scalability 40

O'Reilly Software

APRIL 4, 2018

Considerations for setting the architectural foundations for a fast data platform. Google was among the pioneers that created “web scale” architectures to analyze the massive data sets that resulted from “crawling” the web that gave birth to Apache Hadoop, MapReduce, and NoSQL databases. Back in the days of Web 1.0, At least once?

Architecture 80

Architecture Scalability Google Operating System 80

HammerDB

OCTOBER 12, 2018

As is also the case this limitation is at the database level (especially the storage engine) rather than the hardware level. driver: intel_pstate CPUs which run at the same hardware frequency: 0 . hardware limits: 1000 MHz - 3.80 GHz available cpufreq governors: performance powersave . current CPU frequency: 1.99

Best Practices 40

Best Practices Scalability Performance C++ 40

SQL Server According to Bob

JANUARY 11, 2020

Example 1: ​​ Hardware failure (CPU board) Battery backup on the caching controller maintained the data. Important Always consult with your hardware manufacturer for proper stable media strategies. For specific information on I/O tuning and balancing, you will find more details in the following document.

Servers 40

Servers Cache Media Hardware 40

John McCalpin

JANUARY 22, 2018

Since “peak performance” for the processor is two (512-bit SIMD) FMA instructions per cycle, any instructions that are not FMA instructions subtract directly from the available peak performance. of the “adjusted peak performance”, there is no longer a significant upside to performance tuning.

Latency 40

Latency Hardware Code Testing 40

SQL Performance

MARCH 8, 2021

This can make it difficult to draw sound performance-tuning conclusions. This uses hardware, typically a crystal oscillator, that produces ticks at a very high constant rate regardless of processor speed, power settings, or anything of that nature. We can do the correct offset calculation manually using the data available in the plan.

Servers 95

Servers Tuning Architecture Processing 95

Percona

NOVEMBER 3, 2023

Rather than listing the concepts, function calls, etc, available in Citus, which frankly is a bit boring, I’m going to explore scaling out a database system starting with a single host. A future blog will continue my exploration into Citus by scaling out pgbench into other architectures.

Database 104

Database Benchmarking Latency C++ 104

High Scalability

NOVEMBER 25, 2019

Over time, costs for S3 and GCS became reasonable and with Egnyte’s storage plugin architecture, our customers can now bring in any storage backend of their choice. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. SOA architecture based on REST APIs. Edge caching.

Architecture 52

Architecture Cache Azure Storage 52

John McCalpin

APRIL 25, 2023

Multicore processors have huge amounts of available DRAM bandwidth – maybe it does not even make sense for a single core to try to use that much? Stay tuned! link] ) For the single-core case the bandwidth reported by the STREAM benchmark kernels is very close to the same as the bandwidth for the all-read tests reported here.

Benchmarking 97

Benchmarking Cache Latency Tuning 97