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. Every time the trigger executes, the function runs on an available resource. How does serverless computing tackle inefficiencies?

Serverless 246

Serverless Efficiency Lambda AWS 246

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. This is especially the case with microservices and applications created around multiple tiers, where cheaper hardware alternatives play a significant role in the infrastructure footprint.

Java 182

Java Hardware Metrics Tuning 182

Dynatrace

SEPTEMBER 29, 2021

Container technology is very powerful as small teams can develop and package their application on laptops and then deploy it anywhere into staging or production environments without having to worry about dependencies, configurations, OS, hardware, and so on. The time and effort saved with testing and deployment are a game-changer for DevOps.

Open Source 334

Open Source DevOps Traffic Cloud 334

Dynatrace

AUGUST 12, 2020

Dynatrace is thrilled to announce the General Availability of support for both the 2.x With Azure Functions, engineers don’t have to worry about provisioning and maintaining underlying hardware; they simply upload their code, and it’s up and running seconds later. So stay tuned! What’s next.

Serverless 246

Serverless Azure Monitoring Lambda 246

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. Today they are available in: US East (N.

Availability 122

Availability Performance Scalability AWS 122

Dynatrace

APRIL 21, 2023

The Office of the CTO wanted to ensure a positive citizen experience by identifying the 200+ critical applications available within their 21 executive agencies and offering application performance monitoring (APM) as a service to those agencies. Zbojniewicz wanted to drive APM and simultaneously decommission the legacy toolset successfully.

Government 239

Government Infrastructure Innovation Monitoring 239

Dynatrace

OCTOBER 24, 2019

As an application owner, you need to ensure the continuous availability and performance of your applications from your end-users’ point of view. Sometimes, you need to check the availability of internal resources that aren’t accessible from outside your network. More information is available in Dynatrace Help.

Hardware 30

Hardware Monitoring Tuning Network 30

Dynatrace

AUGUST 10, 2019

Having the ability to monitor the performance and availability of your organization’s internal applications—in addition to your organization’s customer-facing applications—from within your corporate network is an important benefit of synthetic monitoring. Compliance with hardware requirements. Dynatrace news.

Monitoring 150

Monitoring Hardware Tuning Mobile 150

The Netflix TechBlog

NOVEMBER 9, 2021

AV1 playback on TV platforms relies on hardware solutions, which generally take longer to be deployed. Throughout 2020 the industry made impressive progress on AV1 hardware solutions. The Encoding Technologies team took a first stab at this problem by fine-tuning the encoding recipe. Stay tuned!

Media 246

Media Open Source Software Engineering Efficiency 246

Percona

MARCH 23, 2023

Hardware Memory The amount of RAM to be provisioned for database servers can vary greatly depending on the size of the database and the specific requirements of the company. Typically a good value is 70%-80% of available memory. If you see concurrency issues, you can tune this variable.

Performance 144

Performance Hardware Tuning Storage 144

Dynatrace

AUGUST 12, 2020

Dynatrace is thrilled to announce the General Availability of support for both the 2.x With Azure Functions, engineers don’t have to worry about provisioning and maintaining underlying hardware; they simply upload their code, and it’s up and running seconds later. So stay tuned! What’s next.

Serverless 217

Serverless Azure Monitoring Lambda 217

Percona

AUGUST 29, 2018

In this post, we will discuss some important kernel parameters that can affect database server performance and how these should be tuned. vm.overcommit_ratio is the percentage of RAM that is available for overcommitment. There are no “good” values for these two parameters since both depend on the hardware.

Tuning 79

Tuning Database Servers Processing 79

Dynatrace

NOVEMBER 15, 2021

Logs can include data about user inputs, system processes, and hardware states. Log analysis can reveal potential bottlenecks and inefficient configurations so teams can fine-tune system performance. “Logging” is the practice of generating and storing logs for later analysis. Optimized system performance.

Analytics 264

Analytics Monitoring DevOps Artificial Intelligence 264

The Netflix TechBlog

AUGUST 30, 2021

Complementing the hardware is the software on the RAE and in the cloud, and bridging the software on both ends is a bi-directional control plane. For example, when running tests, the state of the device will change from “available for testing” to “in test.” In this blog post, we will focus on the latter feature set.

Latency 222

Latency Traffic Transportation Cloud 222

All Things Distributed

MARCH 19, 2018

Amazon SageMaker training supports powerful container management mechanisms that include spinning up large numbers of containers on different hardware with fast networking and access to the underlying hardware, such as GPUs. Post-training model tuning and rich states. This can all be done without touching a single line of code.

Scalability 127

Scalability Hardware AWS Tuning 127

The Morning Paper

NOVEMBER 3, 2019

Perhaps the most interesting lesson/reminder is this: it takes a lot of effort to tune a Linux kernel. Google’s data center kernel is carefully performance tuned for their workloads. On the exact same hardware, the benchmark suite is then used to test 36 Linux release versions from 3.0 Headline results.

Performance 108

Performance Benchmarking Tuning Hardware 108

Percona

SEPTEMBER 1, 2023

While there is no magic bullet for MySQL performance tuning, there are a few areas that can be focused on upfront that can dramatically improve the performance of your MySQL installation. What are the Benefits of MySQL Performance Tuning? A finely tuned database processes queries more efficiently, leading to swifter results.

Tuning 52

Tuning Database Performance Hardware 52

Percona

AUGUST 27, 2018

Resource groups permit assigning threads running within MySQL to particular groups so that threads execute according to the resources available to this group. assigning to a specific CPU) is a manageable resource, represented by the concept of “virtual CPU” as a term that includes CPU cores, hyperthreads, hardware threads, and so forth.

Tuning 70

Tuning Virtualization Testing Servers 70

SQL Performance

JANUARY 23, 2020

Tom Davidson, Opening Microsoft's Performance-Tuning Toolbox SQL Server Pro Magazine, December 2003. Waits and Queues has been used as a SQL Server performance tuning methodology since Tom Davidson published the above article as well as the well-known SQL Server 2005 Waits and Queues whitepaper in 2006. The Top Queries That Weren't.

Tuning 115

Tuning Servers Monitoring Hardware 115

Percona

MAY 1, 2023

Out of the box, the default PostgreSQL configuration is not tuned for any particular workload. It is primarily the responsibility of the database administrator or developer to tune PostgreSQL according to their system’s workload. What is PostgreSQL performance tuning? Why is PostgreSQL performance tuning important?

Tuning 52

Tuning Database Efficiency Performance 52

Dynatrace

OCTOBER 22, 2019

Ultimately, it leads to a state where your system won’t be able to process more data even if you add more hardware. On this page, the difference from a typical thread dump becomes obvious: the data is continuously available, with historical context, and doesn’t need to be triggered if a problem occurs.

Java 145

Java Scalability Hardware Code 145

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. How are we able to do this? This was the genesis of NoSQL databases like Dynamo at Amazon.

Ecommerce 119

Ecommerce Storage Scalability Database 119

Percona

MARCH 27, 2023

The percentage in degradation will vary depending on many factors {hardware, workload, number of tables, configuration, etc.}. Disclaimer : This blog post is meant to show a less-known problem but is not meant to be a serious benchmark. Setup The setup consists of creating 10K tables with sysbench and adding 20 FKs to 20 tables.

Cache 124

Cache Hardware Servers Benchmarking 124

O'Reilly

MARCH 11, 2025

These smaller distilled models can run on off-the-shelf hardware without expensive GPUs. And they can do useful work, particularly if fine-tuned for a specific application domain. The same model will run in the cloud at a reasonable cost without specialized servers.

Artificial Intelligence 63

Artificial Intelligence Infrastructure Government Open Source 63

O'Reilly

NOVEMBER 28, 2023

A year after the first web servers became available, how many companies had websites or were experimenting with building them? That pricing won’t be sustainable, particularly as hardware shortages drive up the cost of building infrastructure. Certainly not two-thirds of them. We’ll say more about this later.) AI will be the same.

Open Source 137

Open Source Google Artificial Intelligence Infrastructure 137

Percona

OCTOBER 18, 2023

Resource allocation: Personnel, hardware, time, and money The migration to open source requires careful allocation (and knowledge) of the resources available to you. Evaluating your hardware requirements is another vital aspect of resource allocation. Look closely at your current infrastructure (hardware, storage, networks, etc.)

Open Source 111

Open Source Database Hardware Strategy 111

Percona

DECEMBER 27, 2023

All of the database automation for running a highly available, resilient, and secure database is built into the operator to simplify the operation and management of your clusters. It comprises numerous organizations from various sectors, including software, hardware, nonprofit, public, and academic.

Cloud 113

Cloud Open Source Strategy Best Practices 113

The Morning Paper

JUNE 27, 2019

The thrust of the argument is that there’s a chain of inter-linked assumptions / dependencies from the hardware all the way to the programming model, and any time you step outside of the mainstream it’s sufficiently hard to get acceptable performance that researchers are discouraged from doing so.

Systems 87

Systems Programming Tuning Innovation 87

Percona

JANUARY 4, 2024

Flexible location : Data files can reside within the MySQL data directory or an independent location, enabling finer control over storage management and performance tuning. For instance: mysql> show create table authorsG 1. mysql> ALTER TABLE authors ENCRYPTION='Y'; Query OK, 0 rows affected (0.05

Storage 114

Storage Engineering Database Open Source 114

The Morning Paper

NOVEMBER 10, 2019

An out-of-band mechanism (tcp socket) is used to advertise the available wire protocol versions when connecting to a remote machine, and the lowest common denominator will be used. The ability to rapidly deploy new versions of Pony Express significantly aided development and tuning of congestion control.

Network 92

Network Transportation Latency Entertainment 92

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. I won’t cover all the features but show just enough that you’ll want to see more of what you can learn to accomplish for yourself.

Database 114

Database Benchmarking Latency C++ 114

Sutter's Mill

NOVEMBER 11, 2023

Instead, you want a library that is tuned for your target hardware architecture and ready for par_unseq vectorized algorithms, for blazing speed. It’s quite possible we may see implementations available sooner, as we do with other popular in-demand draft standard features. This is that library.

C++ 130

C++ Lambda Network Programming 130

The Morning Paper

MAY 21, 2019

Zswap is readily available and runs as a swap device in the Linux kernel. Using zswap means that no new hardware solutions are required, enabling rapid deployment across clusters. Using zswap means that no new hardware solutions are required, enabling rapid deployment across clusters. ML-based auto-tuning. Evaluation.

Software 78

Software Software Google Hardware 78

Scalegrid

JANUARY 25, 2024

It’s important to note that recommended throughput levels may vary depending on factors such as operating system type, network bandwidth availability, and hardware quality. Best Practices for Redis Performance Tuning Optimizing memory allocation is essential for improving Redis’s performance.

Metrics 130

Metrics Monitoring Latency Cache 130

Scalegrid

AUGUST 30, 2024

This fine-tunes operational access inside RabbitMQ and facilitates complex naming conventions for resources and sophisticated rules regarding access. When persistent messages in RabbitMQ are encrypted, it ensures that even in the event of unsanctioned access to storage hardware, confidential information stays protected and secure.

Transportation 130

Transportation Virtualization Strategy Storage 130

The Morning Paper

JUNE 13, 2019

As we saw with the SOAP paper last time out, even with a fixed model variant and hardware there are a lot of different ways to map a training workload over the available hardware. Different hardware architectures (CPUs, GPUs, TPUs, FPGAs, ASICs, …) offer different performance and cost trade-offs.

Hardware 58

Hardware Latency Serverless Energy 58

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