Dynatrace

OCTOBER 7, 2021

This means you no longer have to provision, scale, and maintain servers to run your applications, databases, and storage systems. Speed is next; serverless solutions are quick to spin up or down as needed, and there are no delays due to limited storage or resource access. AWS offers four serverless offerings for storage.

Serverless 286

Serverless AWS Lambda Storage 286

Percona

APRIL 24, 2023

The more indexes, the more the requirement of memory for effective caching. Indexes need more cache than tables Due to random writes and reads, indexes need more pages to be in the cache. Cache requirements for indexes are generally much higher than associated tables. This helps in crash recovery and replication.

Tuning 125

Tuning Cache Storage Database 125

Scalegrid

JANUARY 5, 2024

The DBMS is key to maintaining these aspects by offering a storage system that allows users to perform operations such as data insertion, deletion, and selection, thereby promoting enhanced data integration across diverse applications and platforms. This ultimately results in improving operations and boosting productivity and efficiency.

Efficiency 147

Efficiency Storage Database Scalability 147

The Netflix TechBlog

MAY 4, 2023

This blog post will provide a detailed analysis of replay traffic testing, a versatile technique we have applied in the preliminary validation phase for multiple migration initiatives. After replaying the requests, this dedicated service also records the responses from the production and replay paths for offline analysis.

Traffic 339

Traffic Latency Tuning Systems 339

Dynatrace

DECEMBER 13, 2023

This includes how quickly the application loads, how much load it is putting on the device, how much storage is being used, and how frequently it crashes. This can be achieved by reducing the size of files or images, using caching, and compressing data. Optimize images and videos.

Best Practices 203

Best Practices Mobile Metrics Performance 203

Dynatrace

SEPTEMBER 13, 2023

The Site Reliability Guardian also helps keep your production environment safe and secure through automated change impact analysis. Storing frequently accessed data in faster storage, usually in-memory caching, improves data retrieval speed and overall system performance. Beyond We’d love to hear your suggestions and ideas.

AWS 252

AWS Efficiency Azure Cloud 252

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

Dynatrace

DECEMBER 20, 2021

And why isn’t statistical analysis enough? While data analysis tools such as Google Analytics provide statistics based on user experiences, they lack details about what the user is doing and experiencing. Streamlined asset caching: Asset caching is critical for creating accurate replays. But what is session replay?

Mobile 251

Mobile Website Analytics Cache 251

Brendan Gregg

APRIL 14, 2022

PMC analysis (2017). On the Netflix Java/Linux/EC2 stack there were no working mixed-mode flame graphs, no production safe dynamic tracer, and no PMCs: All tools I used extensively for advanced performance analysis. A large and unexpected opportunity has come my way outside of Netflix that I've decided to try. offer letter logo (2014).

Java 145

Java Cloud Cache AWS 145

Percona

JUNE 22, 2023

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. query cache: Disable (query_cache_size: 0, query_cache_type:OFF) innodb_adaptive_hash_index: Check adaptive hash index usage to determine its efficiency.

Performance 103

Performance Monitoring Traffic Database 103

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

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

ScaleOut Software

MAY 15, 2014

For example, the IMDG must be able to efficiently create millions of objects in each server to make use of its huge storage capacity. Given all this, we thought it would be a good opportunity to see how we are doing relative to the competition, and in particular, relative to Microsoft’s AppFabric caching for Windows on-premise servers.

Cache 40

Cache Servers Network Design 40

Percona

SEPTEMBER 1, 2023

Inadequate CPU, memory, or storage can lead to bottlenecks and performance degradation, so remedying these issues involves upgrading hardware or optimizing resource utilization through query and server configuration adjustments. Query plan analysis can also provide valuable insights.

Tuning 52

Tuning Database Performance Hardware 52

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

Dynatrace

NOVEMBER 5, 2019

User analysis – Adding a JavaScript tag into the applications front end pages enables the collection of front-end load times of the applications. Session Replay – Record user sessions in real-time, with the ability to replay the session to find the root cause of the problem, and usability analysis.

Azure 139

Azure Artificial Intelligence Metrics Innovation 139

Dynatrace

OCTOBER 15, 2021

OpenTelemetry (also referred to as OTel) is an open-source observability framework made up of a collection of tools, APIs, and SDKs, that enables IT teams to instrument, generate, collect, and export telemetry data for analysis and understand software performance and behavior. This occurs once data is safely stored within a local cache.

Open Source 224

Open Source Metrics Cloud Transportation 224

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

Dynatrace

SEPTEMBER 17, 2019

PostgreSQL & Elastic for data storage. REDIS for caching. Robert’s AWS & EKS admin team are monitoring most services with that capability but found it beneficial for them to have Dynatrace monitor Elastic File Storage (EFS). Their technology stack looks like this: Spring Boot-based Microservices. NGINX as an API Gateway.

AWS 128

AWS Monitoring Ecommerce Lambda 128

ScaleOut Software

JULY 21, 2020

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Instead of querying objects from the IMDG and analyzing them in the client, applications can now simply run this analysis within the IMDG itself using APIs available in ScaleOut StateServer Pro.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache. Instead of querying objects from the IMDG and analyzing them in the client, applications can now simply run this analysis within the IMDG itself using APIs available in ScaleOut StateServer Pro.

Analytics 52

Analytics Airlines Cache Scalability 52

Brendan Gregg

APRIL 14, 2022

offer letter logo (2014) flame graphs (2014) eBPF tools (2014-2019) PMC analysis (2017) my pandemic-abandoned desk (2020); office wall I joined Netflix in 2014, a company at the forefront of cloud computing with an attractive work culture. Netflix has been the best job of my career so far, and I'll miss my colleagues and the culture.

Java 52

Java Cache Cloud AWS 52

The Morning Paper

MARCH 10, 2020

This benchmark can synthetically generate more precise key-value queries that represent the reads and writes of key-value stores to the underlying storage system. The paper examines three different uses of RocksDB at Facebook: UDB , the underlying storage engine for the MySQL databases storing the social graph data. Three workloads.

Benchmarking 59

Benchmarking Storage Cache Open Source 59

Randon ASCII

SEPTEMBER 8, 2019

Sometimes the challenge in trace analysis is to find where the issue is, but for this issue that part of the analysis was trivial. Now that we suspect file I/O it’s necessary to go to Graph Explorer-> Storage-> File I/O. This means that there is no caching between RuntimeBroker.exe and this file.

Latency 79

Latency Cache Programming Operating System 79

SQL Performance

NOVEMBER 18, 2019

IT professionals are familiar with scoping the size of VMs with regards to vCPU, memory, and storage capacity. Memory optimized – High memory-to-CPU ratio, relational database servers, medium to large caches, and in-memory analytics. Storage optimized – High disk throughput and IO. Premium storage support. Generation.

Azure 76

Azure Benchmarking Storage Virtualization 76

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

The Morning Paper

APRIL 9, 2019

Does your web application make use of local storage? If so, then like many developers you may well be making the assumption that when you read from local storage, it will only contain the data that you put there. There are two basic requirements for a storage-based XSS attack. As Steffens et al. no sanitisation) at a sink.

Storage 44

Storage Cache Network Transportation 44

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. GHz, 128MB of L3 cache, 128 PCIe 4.0

Azure 72

Azure Virtualization Servers Storage 72

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

Brendan Gregg

JUNE 30, 2018

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. Answering this usually requires analysis using other observability tools while the benchmark is running (what I call "[active benchmarking]"). ### 2. Don't do it. Do it less.

Benchmarking 54

Benchmarking Latency Cache Network 54

High Scalability

NOVEMBER 25, 2019

It is limited by the disk space; it can’t expand storage elastically; it chokes if you run few I/O intensive processes or try collaborating with 100 other users. 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.

Architecture 52

Architecture Cache Azure 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

ACM Sigarch

DECEMBER 6, 2018

To foster research in these categories, we provide an overview of each of these categories to understand the implications on workload analysis and HW/SW architecture research. Architectural research in these areas remains traditionally focused on the analysis of object detection and recognition algorithms (e.g. Yolo , ResNet50 ).

Wireless 54

Wireless IoT Analytics Architecture 54

Smashing Magazine

SEPTEMBER 20, 2021

We think of web scraping as a tool used to harvest web content for information analysis purposes, sometimes to the detriment of the site owner. Search Engine And Web Archive Cached Results. Another common category of imposter domains are domains used by search engines for delivering cached results or archived versions of page views.

Website 89

Website Analytics Google Cache 89

Brendan Gregg

JUNE 29, 2018

A co-worker introduced me to Craig Hanson and Pat Crain's performance mantras, which neatly summarize much of what we do in performance analysis and tuning. Answering this usually requires analysis using other observability tools while the benchmark is running (what I call "[active benchmarking]"). ### 2. Don't do it. Do it less.

Benchmarking 40

Benchmarking Latency Cache Network 40

O'Reilly Software

JUNE 12, 2018

This meant a lot of time was spent on things like cycle time analysis, build pipeline design, test automation, and infrastructure automation. One of the most intriguing is the idea of “turning the database inside out” where the internal sub-components of a database—storage, log, cache and view—are broken into parts and deployed separately.

Database 72

Database Cache Architecture Latency 72

All Things Distributed

JUNE 21, 2018

This consistent performance is a big part of why the Snapchat Stories feature , which includes Snapchat's largest storage write workload, moved to DynamoDB. Expedia built a real-time data warehouse for the market pricing of lodging and availability data for internal market analysis by using Aurora, Amazon Redshift, and ElastiCache.

Database 167

Database AWS Games Latency 167