Dynatrace

SEPTEMBER 15, 2020

Dynatrace can help customers monitor, troubleshoot, and optimize application performance for workloads operating on AWS Outposts, in AWS Regions, and on customer-owned hardware for a truly consistent hybrid experience.”. Joshua Burgin, General Manager, AWS Outposts, Amazon Web Services, Inc. What is AWS Outposts?

AWS 207

AWS Design Storage Cloud 207

Scalegrid

DECEMBER 21, 2023

Such as: RedisInsight – Offers an easy way for users to oversee their Redis® information with visual cues; Prometheus – Providing long-term metrics storage solutions when tracking performance trends involving your instances; Grafana – Its user-friendly interface allows advanced capabilities in observing each instance.

Strategy 130

Strategy Monitoring Latency DevOps 130

Dynatrace

JANUARY 16, 2023

On-premises data centers invest in higher capacity servers since they provide more flexibility in the long run, while the procurement price of hardware is only one of many cost factors. Redis is an in-memory key-value store and cache that simplifies processing, storage, and interaction with data in Kubernetes environments.

Open Source 349

Open Source Java Operating System Programming 349

Dynatrace

JUNE 25, 2020

Our Premium High Availability comes with the following features: Active-active deployment model for optimum hardware utilization. Save on costs for hardware and network bandwidth to optimize total cost of ownership. A similar analysis can be performed on your GRO. A similar analysis can be performed on your GRO.

Availability 253

Availability Hardware Latency Traffic 253

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 is log monitoring?

Analytics 218

Analytics Monitoring Artificial Intelligence DevOps 218

All Things Distributed

SEPTEMBER 20, 2013

Not everybody agreed that the "N-ary Storage Model" (NSM) was the best approach for all workloads but it stayed dominant until hardware constraints, especially on caches, forced the community to revisit some of the alternatives. A Decomposition Storage Model , George P. Copeland and Setrag N.

Storage 87

Storage Hardware Cache C++ 87

O'Reilly

SEPTEMBER 19, 2023

It progressed from “raw compute and storage” to “reimplementing key services in push-button fashion” to “becoming the backbone of AI work”—all under the umbrella of “renting time and storage on someone else’s computers.” Cloud computing? And, often, to giving up.

Hardware 97

Hardware Storage Big Data Blockchain 97

Dynatrace

NOVEMBER 11, 2020

Easier rollout thanks to log storage best practices. Easier rollout thanks to log storage best practices. The migration of the logs storage directory will happen automatically upon the update to OneAgent version 1.203; so there is really nothing you need to do. Advanced customization of OneAgent deployments made easy.

Best Practices 206

Best Practices Storage Java Benchmarking 206

Brendan Gregg

JULY 4, 2021

AWS Graviton2); for memory with the arrival of DDR5 and High Bandwidth Memory (HBM) on-processor; for storage including new uses for 3D Xpoint as a 3D NAND accelerator; for networking with the rise of QUIC and eXpress Data Path (XDP); and so on. I also wrote about these topics in detail for my recent [Systems Performance 2nd Edition] book.

Performance 140

Performance Latency Hardware Storage 140

Percona

JUNE 22, 2023

long_query_time: Defines the threshold for query execution time, and queries taking longer than this threshold are considered slow and logged for further analysis innodb_buffer_pool_size: Sets the size of the InnoDB buffer pool. The point we’re making here is they are critical for MySQL Performance.

Performance 104

Performance Monitoring Traffic Database 104

High Scalability

OCTOBER 24, 2022

Cloud Infrastructure Services -- An analysis of potentially anti-competitive practices by Professor Frédéric Jenny. Each cloud-native evolution is about using the hardware more efficiently. Nitro is a revolutionary combination of purpose-built hardware and software designed to provide performance and security.

Cloud 187

Cloud Hardware Infrastructure Innovation 187

Percona

SEPTEMBER 1, 2023

This results in expedited query execution, reduced resource utilization, and more efficient exploitation of the available hardware resources. This not only enhances performance but also enables you to make more efficient use of your hardware resources, potentially resulting in cost savings on infrastructure.

Tuning 52

Tuning Database Performance Hardware 52

Percona

JUNE 22, 2023

Defining high availability In general terms, high availability refers to the continuous operation of a system with little to no interruption to end users in the event of hardware or software failures, power outages, or other disruptions. If a primary server fails, a backup server can take over and continue to serve requests.

Availability 108

Availability Database Open Source Hardware 108

Scalegrid

JANUARY 25, 2024

These can help you ensure your system’s health and quickly perform root cause analysis of any performance-related issue you might be encountering. 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.

Metrics 130

Metrics Monitoring Latency Cache 130

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 92

Open Source Database Hardware Strategy 92

ScaleOut Software

JULY 27, 2018

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

Scalability 40

Scalability Cache Airlines Healthcare 40

SQL Performance

DECEMBER 17, 2019

This removes the burden of purchasing and maintaining your hardware, storage and networking infrastructure, while still giving you a very familiar experience with Windows and SQL Server itself. There are also large differences in storage capacity and throughput between these extremes.

Azure 72

Azure Virtualization Servers Storage 72

ScaleOut Software

JULY 27, 2018

Hosted on commodity clusters or cloud infrastructures, IMDGs harness the power of distributed computing to deliver scalable storage capacity and access throughput, along with integrated high availability. Looking beyond distributed caching, it’s their ability to perform data-parallel analysis that gives IMDGs such exciting capabilities.

Scalability 40

Scalability Cache Airlines Healthcare 40

Percona

JANUARY 17, 2023

In terms of storage, internal pages are no different than the root page; they also store pointers to other internal pages. The majority of issues are caused by hardware failure or hardware issues, and the following are the most probable reasons. If this page is corrupted or inaccessible, it is impossible to access the index.

Database 118

Database Hardware Storage Programming 118

Scalegrid

JULY 13, 2020

pg_repack – reorganizes tables online to reclaim storage. PostgreSQL offers more light-weight tuning capabilities, like their Query Optimizer, and DBaaS platforms like ScaleGrid offer advanced slow query analysis. Oracle support for hardware and software packages is typically available at 22% of their licensing fees.

Open Source 244

Open Source Tuning C++ Database 244

Percona

JULY 7, 2023

Also, in general terms, a high availability PostgreSQL solution must cover four key areas: Infrastructure: This is the physical or virtual hardware database systems rely on to run. Can you afford the necessary hardware, software, and operational costs of maintaining a PostgreSQL HA solution? there cannot be high availability.

Availability 84

Availability Open Source Architecture Database 84

Brendan Gregg

JULY 4, 2021

AWS Graviton2); for memory with the arrival of DDR5 and High Bandwidth Memory (HBM) on-processor; for storage including new uses for 3D Xpoint as a 3D NAND accelerator; for networking with the rise of QUIC and eXpress Data Path (XDP); and so on. I also wrote about these topics in detail for my recent [Systems Performance 2nd Edition] book.

Performance 52

Performance Latency Hardware Storage 52

The Morning Paper

FEBRUARY 20, 2020

… based on interactions with enterprise customers, we expect that storage and inference of ML models will be subject to the same scrutiny and performance requirements of sensitive/mission-critical operational data. Static analysis and the IR. It can’t handle loops for example (an analysis of 4.6M pruning).

Processing 72

Processing Hardware Database Azure 72

Brendan Gregg

FEBRUARY 28, 2023

## References I've reproduced the references from my SREcon22 keynote below, so you can click on links: - [Gregg 08] Brendan Gregg, “ZFS L2ARC,” [link] Jul 2008 - [Gregg 10] Brendan Gregg, “Visualizations for Performance Analysis (and More),” [link] 2010 - [Greenberg 11] Marc Greenberg, “DDR4: Double the speed, double the latency?

Performance 110

Performance Latency Cache Virtualization 110

The Morning Paper

FEBRUARY 18, 2020

The core idea is to continuously monitor all aspects of the business, actively interpret the observations using advanced data analysis – including ML – and integrate the learnings into appropriate actions that improve business outcomes.

Government 95

Government Software Engineering Storage Database 95

All Things Distributed

OCTOBER 7, 2015

In such a data intensive environment, making key business decisions such as running marketing and sales campaigns, logistic planning, financial analysis and ad targeting require deriving insights from these data. We live in a world where massive volumes of data are generated from websites, connected devices and mobile apps.

Cloud 137

Cloud Big Data AWS Analytics 137

The Morning Paper

OCTOBER 4, 2020

It’s a great analysis that taught me a lot about the realities of 5G, and the challenges ahead if we are to eventually get there. Three different 5G phones are used, including a ZTE Axon10 Pro with powerful communication (SDX 50 5G modem) and compute (Qualcomm Snapdragon TM855) capabilities together with 256GB of storage.

Energy 130

Energy Latency Performance Network 130

Percona

DECEMBER 14, 2022

Suppose you are performing a deep-dive analysis involving a table of records containing 50 columns. The CITUS columnar extension feature set includes: Highly compressed tables: Reduces storage requirements. Columnar storage. What follows here are the results of my analysis. Reduces the IO needed to scan the table.

Database 92

Database Analytics Storage Processing 92

Brendan Gregg

FEBRUARY 28, 2023

References I've reproduced the references from my SREcon22 keynote below, so you can click on links: [Gregg 08] Brendan Gregg, “ZFS L2ARC,” [link] , Jul 2008 [Gregg 10] Brendan Gregg, “Visualizations for Performance Analysis (and More),” [link] , 2010 [Greenberg 11] Marc Greenberg, “DDR4: Double the speed, double the latency?

Performance 52

Performance Latency Cache Virtualization 52

All Things Distributed

AUGUST 16, 2012

An apples to apples comparison of the costs associated with running various usage patterns on-premises and with AWS requires more than a simple comparison of hardware expense versus always-on utility pricing for compute and storage. s a summary chart of the TCO analysis. What this chart summarizes is that.

AWS 118

AWS Hardware Traffic Best Practices 118

All Things Distributed

MARCH 11, 2015

In the past analytics within an organization was the pinnacle of old style IT: a centralized data warehouse running on specialized hardware. This is being called Video Content Analysis (VCA) and it has many application areas from retail to transportation. Teams are using video analysis to process many different angles on the players.

Analytics 135

Analytics Cloud Healthcare Retail 135

The Morning Paper

SEPTEMBER 19, 2019

Autoscaling tiered cloud storage in Anna. Could it be Analyzing efficient stream processing on modern hardware ? On one of the themes that captures my imagination, how changing hardware platform influence system design: Rethinking database high availability with RDMA networks. Research papers. (In In random order!).

Blockchain 46

Blockchain Hardware Google Analytics 46

Percona

AUGUST 29, 2023

Its query engine not only parallelizes incoming SQL queries for time series but also has the ability to create column-wise tables making it ideal for OLAP analysis duties. Columnar storage of tables can compress data, speeding up scans and supporting fast projections, both on regular and distributed tables.

C++ 80

C++ Database Storage Testing 80

Adrian Cockcroft

JUNE 21, 2022

I became the Sun UK local specialist in performance and hardware, and as Sun transitioned from a desktop workstation company to sell high end multiprocessor servers I was helping customers find and fix scalability problems. We had specializations in hardware, operating systems, databases, graphics, etc.

Tuning 52

Tuning Benchmarking Engineering C++ 52

Tim Kadlec

JANUARY 9, 2019

Hardware gets better, sure. Ballooning bandwidth and storage have fostered complacency that we can do without. Just how much kWh are expended per one GB of data is up for some debate depending on your method of analysis. Let’s say that you’re one of those people with a device a year or two old. It makes sense.

Performance 111

Performance Energy Internet Internet 111

Dynatrace

AUGUST 5, 2019

It covers these key areas: Technology & Dependency Analysis. Resource consumption & traffic analysis. While most of our cloud & platform partners have their own dependency analysis tooling, most of them focus on basic dependency detection based on network connection analysis between hosts.

Cloud 31

Cloud Traffic Database Network 31

Adrian Cockcroft

NOVEMBER 11, 2019

This discussion focuses on hardware, software and operational failure modes. This is effectively a top-down approach to failure mode analysis, and it avoids the trap of getting bogged down in all the possible things that could go wrong using a bottoms-up approach. Book: Engineering a Safer World by Nancy G.

Latency 52

Latency Engineering Systems Hardware 52