Smashing Magazine

SEPTEMBER 28, 2022

Five Data-Loading Patterns To Improve Frontend Performance. Five Data-Loading Patterns To Improve Frontend Performance. Data loading patterns are an essential part of your application as they will determine which parts of your application are directly usable by visitors. But isn’t waiting for the data the point?

Cache 125

Cache Performance Servers Social Media 125

Brendan Gregg

JUNE 30, 2018

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

Benchmarking 54

Benchmarking Latency Cache Network 54

n0derunner

JULY 1, 2022

I was recently asked to investigate why Nutanix storage was not as fast as a competing solution in a PoC environment. When I looked at the output from diskspd, the data didn’t quite make sense. appeared first on n0derunner.

Storage 52

Storage Testing Performance Benchmarking 52

Percona

NOVEMBER 3, 2023

When it comes to Citus, successfully building out and scaling a PostgreSQL cluster across multiple nodes and even across data centers can feel, at times, to be an art form because there are so many ways of building it out. The following invocation generates almost 4GB of data.

Database 102

Database Benchmarking Latency C++ 102

The Netflix TechBlog

OCTOBER 19, 2020

Our distributed tracing infrastructure is grouped into three sections: tracer library instrumentation, stream processing, and storage. Traces collected from various microservices are ingested in a stream processing manner into the data store. Stream Processing: to sample or not to sample trace data?

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

Scalegrid

JANUARY 12, 2024

Key Takeaways A cloud workload encompasses any application or service running on a cloud infrastructure, facilitating tasks ranging from basic functions to advanced data analysis with the help of resources like databases, collaboration tools, and disaster recovery systems. This applies to both virtual machines and container-based deployments.

Cloud 130

Cloud Virtualization Storage Efficiency 130

The Morning Paper

NOVEMBER 26, 2019

Mergeable replicated data types – part II Kaki et al., Last time out we saw how Mergeable Replicated Data Types (MRDTs) use a bijection between the natural domain of a data type and relational sets to define merge semantics between two concurrently modified versions given their lowest common ancestor (LCA).

C++ 98

C++ Storage Benchmarking Efficiency 98

Scalegrid

JANUARY 25, 2024

Key metrics like throughput, request latency, and memory utilization are essential for assessing Redis health, with tools like the MONITOR command and Redis-benchmark for latency and throughput analysis and MEMORY USAGE/STATS commands for evaluating memory. It depends upon your application workload and its business logic.

Metrics 130

Metrics Monitoring Latency Cache 130

Dynatrace

NOVEMBER 2, 2020

IT infrastructure is the heart of your digital business and connects every area – physical and virtual servers, storage, databases, networks, cloud services. This shift requires infrastructure monitoring to ensure all your components work together across applications, operating systems, storage, servers, virtualization, and more.

Infrastructure 202

Infrastructure Monitoring Virtualization Serverless 202

Brendan Gregg

JUNE 29, 2018

These have inspired me to summarize another performance activity: evaluating benchmark accuracy. Accurate benchmarking rewards engineering investment that actually improves performance, but, unfortunately, inaccurate benchmarking is more common. If the benchmark reported 20k ops/sec, you should ask: why not 40k ops/sec?

Benchmarking 40

Benchmarking Latency Cache Network 40

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

Scalegrid

DECEMBER 6, 2023

In the digital age, data management has transformed from locally hosted servers to cloud solutions. Though it may be overwhelming, there can still be great appeal when one has control over their own data privacy requirements depending on how customization is desired by the organization itself.

Database 130

Database Cloud Hardware Storage 130

HammerDB

APRIL 19, 2023

As database performance is heavily influenced by the performance of storage, network, memory, and processors, we must understand the upper limit of these key components. For storage, FIO is generally used. Benchmarking the target Two of the more popular database benchmarks for MySQL are HammerDB and sysbench. 0.42 %sys 9.52

Performance 54

Performance Benchmarking Cache Storage 54

Abhishek Tiwari

DECEMBER 27, 2017

Kubernetes has emerged as go to container orchestration platform for data engineering teams. In 2018, a widespread adaptation of Kubernetes for big data processing is anitcipated. Organisations are already using Kubernetes for a variety of workloads [1] [2] and data workloads are up next. better cluster resource utilization.

Big Data 63

Big Data Storage Benchmarking Hardware 63

Dynatrace

NOVEMBER 11, 2020

Dynatrace OneAgent deployment and life-cycle management are already widely considered to be industry benchmarks for reliability and efficiency. Easier rollout thanks to log storage best practices. Easier rollout thanks to log storage best practices. Keeping the runtime data in the /opt directory made it cumbersome to maintain.

Best Practices 199

Best Practices Storage Java Benchmarking 199

Percona

MARCH 23, 2023

Storage The type of storage and disk used for database servers can have a significant impact on performance and reliability. Benchmark before you decide. Cloud Different cloud providers offer a range of instance types and sizes, each with varying amounts of CPU, memory, and storage. Transparent huge pages (THP) disabled.

Performance 123

Performance Hardware Tuning Storage 123

SQL Shack

SEPTEMBER 9, 2019

Index Fill factor SQL Server Index Fill Factor is a percentage value to be filled data page with data in SQL Server. This option is available in index properties to manage data storage in the data pages. In this article, we will study in detail about the how SQL Server Index Fill factor works. It […].

Benchmarking 56

Benchmarking Servers Performance Storage 56

SQL Performance

NOVEMBER 18, 2019

IT professionals are familiar with scoping the size of VMs with regards to vCPU, memory, and storage capacity. Storage optimized – High disk throughput and IO. The sizes offer you options for the number of vCPUs, RAM, and data disks. and the overall size will determine the amount of temporary storage available.

Azure 76

Azure Benchmarking Storage Virtualization 76

n0derunner

OCTOBER 5, 2020

How to speed up your X-ray benchmark development cycle by re-using/re-cycling benchmark VMs and more importantly data-sets. Problem: For large datasets, creating the data on-disk can be time consuming. Assuming we have enough storage bandwidth, the throughput.

Benchmarking 52

Benchmarking Storage Speed Development 52

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 100

AWS Entertainment Open Source Benchmarking 100

The Netflix TechBlog

NOVEMBER 22, 2019

4:45pm-5:45pm NFX 209 File system as a service at Netflix Kishore Kasi , Senior Software Engineer Abstract : As Netflix grows in original content creation, its need for storage is also increasing at a rapid pace. Technology advancements in content creation and consumption have also increased its data footprint.

AWS 100

AWS Entertainment Open Source Benchmarking 100

Percona

DECEMBER 23, 2022

I wrote this post on MyRocks because I believe it is the most interesting new MySQL storage engine to have appeared over the last few years. The use case is the TPC-C benchmark but executed not on a high-end server but on a lower-spec virtual machine that is I/O limited like for example, with AWS EBS volumes. Long term stability.

Storage 55

Storage Cache C++ Virtualization 55

Percona

JUNE 22, 2023

Database uptime and availability Monitoring database uptime and availability is crucial as it directly impacts the availability of critical data and the performance of applications or websites that rely on the MySQL database. Disk space usage Monitor the disk space usage of MySQL data files, log files, and temporary files.

Performance 102

Performance Monitoring Traffic Database 102

HammerDB

JUNE 27, 2022

HammerDB is a software application for database benchmarking. Databases are highly sophisticated software, and to design and run a fair benchmark workload is a complex undertaking. The Transaction Processing Performance Council (TPC) was founded to bring standards to database benchmarking, and the history of the TPC can be found here.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

Percona

APRIL 7, 2023

To illustrate this, I ran the Sysbench-TPCC synthetic benchmark against two different GCP instances running a freshly installed Percona Server for MySQL version 8.0.31 In MySQL, considering the standard storage engine, InnoDB , the data cache is called Buffer Pool. In PostgreSQL, it is called shared buffers.

Tuning 133

Tuning Cache Servers Benchmarking 133

The Morning Paper

SEPTEMBER 15, 2019

Fine-grained, secure and efficient data provenance on blockchain systems Ruan et al., In designing a blockchain-friendly provenance mechanism, three aspects unique to the blockchain environment differentiate the problem from that of traditional database provenance: There are no higher-order data operators (e.g. VLDB’19.

Blockchain 55

Blockchain Efficiency Systems Storage 55

The Morning Paper

AUGUST 29, 2019

There’s a broad set of choices including where you store the data, whether you run your own DBMS nodes or use a service, the kinds of instance types to go for if you do run your own, and so forth. We focused on OLAP-oriented parallel data warehouse products available for AWS and restricted our attention to commercially available systems.

Architecture 76

Architecture Cloud Storage Serverless 76

Particular Software

OCTOBER 26, 2020

If you are already using Cosmos DB to store your business data, you no longer need to use a different storage technology to store your NServiceBus saga data. Getting started is easy To simply store saga data using Cosmos DB, this is all that’s needed: endpointConfiguration.UsePersistence<CosmosDbPersistence>().CosmosClient(new

Azure 52

Azure Storage Benchmarking Latency 52

Percona

JULY 1, 2023

It efficiently manages read and write operations, optimizes data access, and minimizes contention, resulting in high throughput and low latency to ensure that applications perform at their best. These automated features reduce the burden on DBAs and organizations for their data protection efforts by simplifying database backups and recovery.

AWS 52

AWS Database Serverless Storage 52

Percona

MARCH 17, 2023

PMM2 uses VictoriaMetrics (VM) as its metrics storage engine. Please note that the focus of these tests was around standard metrics gathering and display, we’ll use a future blog post to benchmark some of the more intensive query analytics (QAN) performance numbers.

Monitoring 95

Monitoring Scalability Cache Database 95

n0derunner

MAY 6, 2019

A 2007 paper, that still has lots to say on the subject of benchmarking storage and filesystems. Primarily aimed at researchers and developers, but is relevant to anyone about to embark on a benchmarking effort. A Nine year study of filesystem and storage benchmarking Download. The post New (Old) Paper.

Benchmarking 40

Benchmarking Storage Cache Testing 40

HammerDB

NOVEMBER 5, 2018

This post at an entry-level discusses the options you have to improve log throughput in your benchmark environment. . Before the database is started your data should be in a consistent state on disk. When the database is started a component of the in-memory database instance is the data buffer.

Benchmarking 40

Benchmarking Database C++ Virtualization 40

Percona

JULY 25, 2023

When a new node joins the cluster, SST is performed to receive the data from DONOR to the JOINER. JOINER uses PXB to stream the data directory from DONOR. Percona XtraBackup copies the InnoDB data files. Percona XtraBackup copies the InnoDB data files. ibd2sdi data/test/t1.ibd ibd > t1.sdi

Cache 83

Cache Benchmarking Servers Design 83

Percona

JANUARY 19, 2023

With disks being faster nowadays and CPU and memory resources being cheaper, we could easily say MySQL can handle TBs of data with good performance. For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. There are many compression tools and algorithms for data out there.

Open Source 85

Open Source Storage Database Big Data 85

n0derunner

SEPTEMBER 17, 2018

Creating a HCI benchmark to simulate multi-tennent workloads. As with traditional storage, applications are writing to a shared storage environment which is necessary to support VM movement. As with traditional storage, applications are writing to a shared storage environment which is necessary to support VM movement.

Performance Testing 40

Performance Testing Benchmarking Testing Performance 40

Percona

MAY 1, 2023

Hardware optimization : You need to ensure that the CPU, memory, and storage components meet the performance requirements of the database workload. Connection pooling: Minimizing connection overhead and improving response times for frequently accessed data by implementing mechanisms for connection pooling and caching strategies.

Tuning 52

Tuning Efficiency Database Performance 52

n0derunner

DECEMBER 17, 2018

I am using X-Ray to simulate a 1TB data restore into an existing database. bssplit=64k/20:128k/20:256k/20:512k/20:1m/20 Normally storage benchmarks using large IO sizes are performed serially, because it’s easier on the storage back-end.

Performance 64

Performance Benchmarking Storage Network 64