Dynatrace

NOVEMBER 3, 2021

Monitoring focuses on watching specific metrics. Observability is the ability to understand a system’s internal state by analyzing the data it generates, such as logs, metrics, and traces. For example, we can actively watch a single metric for changes that indicate a problem — this is monitoring.

Monitoring 226

Monitoring Metrics DevOps Scalability 226

Dynatrace

AUGUST 1, 2022

Interestingly, our partner RedHat reported in 2021 that around 80% of deployed workloads are databases or data caches, storing data in persistent volume claims (PVCs). You also decide to run your database for storing user uploads – such as images or videos – directly in Kubernetes. However, you lack insights into your PVCs.

Storage 192

Storage Database Network Metrics 192

Percona

SEPTEMBER 1, 2023

MySQL performance tuning offers several significant advantages for effective database management and optimization. Enhanced Database Efficiency By adjusting configuration settings, you can markedly enhance the overall efficiency of your MySQL database. Experiencing database performance issues?

Tuning 52

Tuning Database Performance Hardware 52

Percona

JUNE 22, 2023

To make data count and to ensure cloud computing is unabated, companies and organizations must have highly available databases. A basic high availability database system provides failover (preferably automatic) from a primary database node to redundant nodes within a cluster. HA is sometimes confused with “fault tolerance.”

Availability 104

Availability Database Open Source Hardware 104

Percona

JUNE 22, 2023

As a MySQL database administrator, keeping a close eye on the performance of your MySQL server is crucial to ensure optimal database operations. This includes metrics such as query execution time, the number of queries executed per second, and the utilization of query cache and adaptive hash index.

Performance 102

Performance Monitoring Traffic Database 102

Percona

AUGUST 8, 2023

Hardware considerations The first thing we have to consider here is the resources that the underlying host provides to the database. Global caches like the InnoDB buffer pool and MyISAM key cache and session-level caches like the sort buffer, join buffer, random read buffer, etc. Do these queries use more caches?

Traffic 88

Traffic Cache Monitoring Database 88

Dynatrace

NOVEMBER 29, 2021

When you add the Dynatrace extension to your Lambda functions, Dynatrace begins ingesting their metrics, logs, and traces, which you can monitor and correlate with data from the rest of your stack. In addition to the built-in views, Dynatrace provides data analysis tools that greatly enhance your abilities to query and chart metrics.

Lambda 218

Lambda AWS Serverless Metrics 218

Dynatrace

APRIL 21, 2022

Most monitoring tools for migrations, development, and operations focus on collecting and aggregating the three pillars of observability— metrics, traces, and logs. Getting precise root cause analysis when dealing with several layers of virtualization in a containerized world. Understanding resource utilization for cost management.

Azure 193

Azure Monitoring Virtualization Metrics 193

Dynatrace

AUGUST 30, 2019

Infrastructure Optimization: 100% improvement in Database Connectivity. Missing Cache Settings – Make sure you cache resources that don’t change often on the browser or use a CDN. That included web servers, app services, microservices, queues, databases, mainframe and external services.

Cache 201

Cache Architecture Database Government 201

Percona

NOVEMBER 9, 2023

In this blog post, we will discuss how to extend Percona Monitoring and Management (PMM) to get PostgreSQL metrics on checkpointing activity, internal buffers, and WAL usage. With this data, we’ll be able to better understand and tune our Postgres servers. You can search the blog for more information on this if needed.

Monitoring 87

Monitoring Tuning Metrics Servers 87

Highly Scalable

SEPTEMBER 18, 2012

These developments gradually highlight a system of relevant database building blocks with proven practical efficiency. In this article I’m trying to provide more or less systematic description of techniques related to distributed operations in NoSQL databases. Data Placement. System Coordination. Read/Write latency.

Database 213

Database Latency C++ Scalability 213

Smashing Magazine

AUGUST 3, 2023

Google’s Core Web Vitals is a set of performance metrics that site owners can use to evaluate performance and diagnose performance issues. These metrics provide a different perspective on user experience: Largest Contentful Paint (LCP) Measures the time it takes for the main content on a webpage to load. One of the key Next.js

Performance 75

Performance Cache Traffic Metrics 75

SQL Performance

APRIL 13, 2020

His version can be used for the plan cache – the only challenge there is the information is transient, so you may not capture every query that uses a particular index. value ( '(@Database) [1 ]' , 'varchar(128)' ) AS DatabaseName , obj. value ( '(@StatementText) [1 ]' , 'varchar(max)' ) AS SQL_Text , obj. nodes ( '.

Tuning 137

Tuning Cache Metrics Testing 137

Smashing Magazine

MAY 12, 2022

As I previously mentioned, my primary data source for this analysis is Google CrUX. CrUX is a cloud-based database into which Real User Measurements (RUM) are collected from live Chrome browser sessions. In particular, the collected measurements include the three Core Web Vitals metrics measured for each session.

Google 130

Google Performance Website Mobile 130

Adrian Cockcroft

JANUARY 29, 2023

I presented this analysis of response time distributions talk in 2016 — at Microxchg in Berlin ( video ). I spent a long time trying to figure out how to do this analysis at all, was hopeful that it was an existing technique if I could only find an example. I’ve been thinking about this for a long time.

Lambda 98

Lambda Latency Cache C++ 98

MachMetrics

DECEMBER 14, 2019

Similar to our article Average Page Load Times for 2018 , we’ll go over the averages for metrics and help you determine if your site is faster or slower than average. As you know, there are many metrics that determine a website’s page speed, and we can’t look at just one of them to determine how performant our site is.

Best Practices 105

Best Practices Speed Mobile Google 105

SQL Performance

MARCH 30, 2021

To provide a concrete basis for the analysis, we will follow how a particular parallel query starts execution. I used the public Stack Overflow 2013 database ( download details ). See Myth: SQL Server Caches a Serial Plan with every Parallel Plan for details. Creating cached expression values ( runtime constants ).

Cache 98

Cache Servers Operating System Processing 98

Dynatrace

SEPTEMBER 17, 2019

REDIS for caching. Another important view is the historical data across all nodes, which allows administrators to spot deployment imbalances as well as under or overprovisioned nodes: The node analysis view makes it easy to spot deployment imbalances as well as misconfigured and unhealthy nodes. #3 NGINX as an API Gateway.

AWS 128

AWS Monitoring Ecommerce Lambda 128

The Morning Paper

SEPTEMBER 10, 2019

Broadly, these can be categorized as: reporting and dashboarding, embedded statistics in pages, time-series monitoring, and ad-hoc analysis. Ad-hoc analysis use cases support internal teams performing complex ad-hoc analyses to understand usage trends and determine how to improve products. Cache all the things.

Analytics 75

Analytics Latency Cache Google 75

Particular Software

MAY 8, 2023

ServicePulse also exposes a range of metrics that provide insight into the system’s behavior. Apart from enabling auditing and metrics in your configuration, it doesn’t require any code changes to gather instrumentation from your endpoints. All of these components can participate in a business transaction.

Systems 52

Systems C++ Azure Metrics 52

Alex Russell

MARCH 6, 2021

The scale of the effect can be deeply situational or hard to suss out without solid metrics. A then-representative $200USD device had 4-8 slow (in-order, low-cache) cores, ~2GiB of RAM, and relatively slow MLC NAND flash storage. The Moto G4 , for example. Don't pay a lot for an Android-shaped muffler.

Performance 124

Performance Network Cache Metrics 124

Smashing Magazine

JANUARY 6, 2020

Getting Ready: Planning And Metrics. Getting Ready: Planning And Metrics. You need a business stakeholder buy-in, and to get it, you need to establish a case study, or a proof of concept using the Performance API on how speed benefits metrics and Key Performance Indicators ( KPIs ) they care about. Table Of Contents. Quick Wins.

Performance 145

Performance Cache Network Metrics 145

Brendan Gregg

FEBRUARY 9, 2018

This overhead can be reduced by A) pcid, fully available in Linux 4.14, and B) Huge pages. - **Cache access pattern**: the overheads are exacerbated by certain access patterns that switch from caching well to caching a little less well. At 50k syscalls/sec per CPU the overhead may be 2%, and climbs as the syscall rate increases.

Performance 75

Performance Benchmarking Cache Tuning 75

Brendan Gregg

JANUARY 17, 2018

It is used for capacity planning and scalability analysis. Here is a MySQL database server (mysqld), PID 423, and measuring its working set size for 0.1 Short durations can be useful for understanding how well a WSS will fit into the CPU caches (L1/L2/L3, TLB L1/L2, etc). This is the working set size metric. 16.570 403.66

Cache 71

Cache Latency C++ Programming 71

Brendan Gregg

FEBRUARY 8, 2018

This overhead can be reduced by A) pcid, fully available in Linux 4.14, and B) Huge pages. - **Cache access pattern**: the overheads are exacerbated by certain access patterns that switch from caching well to caching a little less well. At 50k syscalls/sec per CPU the overhead may be 2%, and climbs as the syscall rate increases.

Performance 40

Performance Benchmarking Cache Tuning 40

Brendan Gregg

JANUARY 16, 2018

It is used for capacity planning and scalability analysis. Here is a MySQL database server (mysqld), PID 423, and measuring its working set size for 0.1 Short durations can be useful for understanding how well a WSS will fit into the CPU caches (L1/L2/L3, TLB L1/L2, etc). This is the working set size metric. 16.570 403.66

Cache 40

Cache Latency C++ Programming 40

SQL Performance

MARCH 8, 2021

The following examples use the public Stack Overflow 2013 database ( download details ), with a single index added: CREATE INDEX PP ON dbo. Total elapsed time is 933ms with 6,673ms of CPU time with a warm cache. How row mode metrics are collected. This next example query uses the same database and index as before.

Servers 95

Servers Tuning Architecture Performance 95

Smashing Magazine

NOVEMBER 22, 2021

Better tooling and metrics standardization. Moreover, the industry has primarily standardized on Google’s Core Web Vitals (CWV) performance metrics, and monitoring them is now integrated into services such as the Google Search Console. But which metrics should be measured in order to determine website performance?

Website 128

Website Performance Google Media 128

Alex Russell

APRIL 29, 2021

Another window into this question is provided by the Web Confluence Metrics project. An extension to Service Workers that enables browsers to present users with cached content when offline. A-series chips have run circles around other ARM parts for more than half a decade, largely through gobsmacking amounts of L2/L3 cache per core.

Media 145

Media Games Education Engineering 145

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

High Scalability

NOVEMBER 25, 2019

Edge caching. In general, Egnyte connect architecture shards and caches data at different levels based on: Amount of data. Nginx for disk based caching. Chokepoint : Even sharded Berkeley DB was choking under the stress and there was a database crash with recovery taking hours, it had to be replaced. Disk based caching.

Architecture 52

Architecture Cache Azure Storage 52