High Scalability

JANUARY 11, 2022

from a client it performs two parallel operations: i) persisting the action in the data store ii) publish the action in a streaming data store for a pub-sub model. User Feed Service, Media Counter Service) read the actions from the streaming data store and performs their specific tasks. Data Models. Graph Data Models.

Design 334

Design Media Storage Logistics 334

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. Here are some ways observability data is important to mobile app performance monitoring. Load time and network latency metrics. Issue remediation. Proactive monitoring.

Best Practices 198

Best Practices Mobile Metrics Performance 198

Scalegrid

DECEMBER 21, 2023

In today’s data-driven world, the ability to effectively monitor and manage data is of paramount importance. Redis®, a powerful in-memory data store, is no exception. Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring.

Strategy 130

Strategy Monitoring Latency DevOps 130

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?

Performance 125

Performance Cache Servers Social Media 125

The Netflix TechBlog

MAY 4, 2023

It can happen on an edge API system servicing customer devices, between the edge and mid-tier services, or from mid-tiers to data stores. It provides a good read on the availability and latency ranges under different production conditions. For instance, envision a response payload that delivers media streams for a playback session.

Traffic 339

Traffic Latency Tuning Systems 339

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., Anchored in the primary use case of supporting Google’s YouTube business, what we’re looking at here could well be the future of data processing at Google. Because they had too many data processing systems! ;). VLDB’19. are divided.

Analytics 75

Analytics Latency Cache Google 75

Dynatrace

SEPTEMBER 13, 2023

These workflows also utilize Davis® , the Dynatrace causal AI engine, and all your observability and security data across all platforms, in context, at scale, and in real-time. Storing frequently accessed data in faster storage, usually in-memory caching, improves data retrieval speed and overall system performance. Beyond

AWS 247

AWS Efficiency Azure Cloud 247

Randon ASCII

SEPTEMBER 8, 2019

The fact that this shows up as CPU time suggests that the reads were all hitting in the system cache and the CPU time was the kernel overhead (note ntoskrnl.exe on the first sampled call stack) of grabbing data from the cache. Now that we suspect file I/O it’s necessary to go to Graph Explorer-> Storage-> File I/O.

Latency 79

Latency Cache Programming Operating System 79

The Morning Paper

FEBRUARY 6, 2020

Last week we looked at a function shipping solution to the problem; Cloudburst uses the more common data shipping to bring data to caches next to function runtimes (though you could also make a case that the scheduling algorithm placing function execution in locations where the data is cached a flavour of function-shipping too).

Lambda 98

Lambda Serverless Cache Latency 98

Percona

APRIL 17, 2023

We’ll also go over some best practices for MongoDB security as well as MongoDB data modeling. The CFQ works well for many general use cases but lacks latency guarantees. The deadline excels at latency-sensitive use cases ( like databases ), and noop is closer to no schedule at all.

Best Practices 52

Best Practices Design Tuning Database 52

Percona

MARCH 23, 2023

By caching hot datasets, indexes, and ongoing changes, InnoDB can provide faster response times and utilize disk IO in a much more optimal way. Storage The type of storage and disk used for database servers can have a significant impact on performance and reliability. Setting oom_score_adj to -800.

Performance 129

Performance Hardware Tuning Storage 129

Percona

APRIL 7, 2023

I’ve used a fourth instance to host a PMM server to monitor servers A and B and used the data collected by the PMM agents installed on the database servers to compare performance. In MySQL, considering the standard storage engine, InnoDB , the data cache is called Buffer Pool.

Tuning 138

Tuning Cache Servers Benchmarking 138

The Morning Paper

NOVEMBER 5, 2019

File systems unfit as distributed storage backends: lessons from 10 years of Ceph evolution Aghayev et al., In this case, the assumption that a distributed storage backend should clearly be layered on top of a local file system. What is a distributed storage backend? SOSP’19. This is not surprising in hindsight.

Storage 64

Storage Systems Hardware Efficiency 64

Brendan Gregg

FEBRUARY 28, 2023

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP

Performance 110

Performance Latency Cache Virtualization 110

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 107

Performance Monitoring Traffic Database 107

IO River

NOVEMBER 2, 2023

Movies and TV shows, which constitute 29% of the content, are expected to grow at a CAGR of 15% over the next five years, driving the need for robust CDN infrastructures.‍‍Static Part The major bulk of data transfer in video streaming is static content. Given its unchanging nature, static content is ideal for caching.

Architecture 52

Architecture Performance Internet Internet 52

Percona

SEPTEMBER 1, 2023

This reduction in latency ensures that applications and websites provide a more rapid and responsive user experience. Scalability As your data volume and user base expand, a finely tuned database can seamlessly accommodate increased workloads without compromising performance. Query plan analysis can also provide valuable insights.

Tuning 52

Tuning Database Performance Hardware 52

The Morning Paper

OCTOBER 26, 2020

On the surface this is a paper about fast data ingestion from high-volume streams, with indexing to support efficient querying. Helios also serves as a reference architecture for how Microsoft envisions its next generation of distributed big-data processing systems being built. PVLDB’20. Emphasis mine ).

Cloud 104

Cloud Big Data Latency Architecture 104

The Morning Paper

JUNE 23, 2019

Coupled with stateless application servers to execute business logic and a database-like system to provide persistent storage, they form a core component of popular data center service archictectures. If you want to store time-expiring data that should be shared across application processes, used Memcached or Redis.

Cache 79

Cache Latency Google Lambda 79

High Scalability

JULY 20, 2018

Cliff Click : The JVM is very good at eliminating the cost of code abstraction, but not the cost of data abstraction. That means multiple data indirections mean multiple cache misses. Mark LaPedus : MRAM, a next-generation memory type, is being touted as a replacement for embedded flash and cache applications.

Internet 121

Internet Internet Scalability Automotive 121

The Morning Paper

OCTOBER 4, 2020

We are standing on the eve of the 5G era… 5G, as a monumental shift in cellular communication technology, holds tremendous potential for spurring innovations across many vertical industries, with its promised multi-Gbps speed, sub-10 ms low latency, and massive connectivity. Throughput and latency. energy consumption).

Energy 130

Energy Latency Performance Network 130

IO River

NOVEMBER 2, 2023

Add-on Services - Special services can include capabilities like security features (WAF, Origin Shield), resource capping (rate limiting), image/video optimization, and more.CDN Pricing Examples1) Amazon Cloudfront’s data routing prices are determined according to amount of traffic and region.

Infrastructure 52

Infrastructure Traffic Cache Strategy 52

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

IO River

NOVEMBER 2, 2023

‍Static Part The major bulk of data transfer in video streaming is static content. Yes, these might change based on localization settings, but in terms of storage, it’s still a completely baked cookie that the server can choose to serve or not serve.Whenever a user clicks on an episode, these bits remain unchanged.

Architecture 52

Architecture Performance Internet Internet 52

ScaleOut Software

MAY 15, 2014

We have spent a great deal of time at ScaleOut Software re-architecting our in-memory data grid (IMDG)’s code base to make best use of many cores and large memory. For example, the IMDG must be able to efficiently create millions of objects in each server to make use of its huge storage capacity. Please retry later.

Cache 40

Cache Servers Network Design 40

Abhishek Tiwari

DECEMBER 27, 2017

ETL refers to extract, transform, load and it is generally used for data warehousing and data integration. There are several emerging data trends that will define the future of ETL in 2018. A common theme across all these trends is to remove the complexity by simplifying data management as a whole.

Big Data 49

Big Data Artificial Intelligence Storage Hardware 49

SQL Performance

APRIL 27, 2020

Many of the newer features we have in SQL Server were initially launched in Azure SQL Database, including (but not limited to) Always Encrypted, Dynamic Data Masking, Row Level Security, and Query Store. The basic tier provides up to 5 DTUs with standard storage. DTU Pricing Tier. vCore Pricing Tier. GB per vCore. HyperScale Database.

Azure 55

Azure Database Serverless Hardware 55

Brendan Gregg

FEBRUARY 28, 2023

My personal opinion is that I don't see a widespread need for more capacity given horizontal scaling and servers that can already exceed 1 Tbyte of DRAM; bandwidth is also helpful, but I'd be concerned about the increased latency for adding a hop to more memory. Ford, et al., “TCP

Performance 52

Performance Latency Cache Virtualization 52

The Netflix TechBlog

NOVEMBER 3, 2022

We introduce a caching mechanism in the API gateway layer, allowing us to offload processing from singleton leader elected controllers without giving up strict data consistency and guarantees clients observe. Active data includes jobs and tasks that are currently running. Titus Gateway handles user requests.

Cache 224

Cache Latency Traffic Systems 224

The Morning Paper

MARCH 17, 2020

The data we have collected demonstrate that many of the assumptions that researchers have made about how NVDIMMs would behave and perform are incorrect. higher latency and lower bandwidth)… We have found the actual behavior of Optane DIMMs to be more complicated and nuanced than the "slower, persistent DRAM" label would suggest.

Scalability 59

Scalability Latency Cache Media 59

IO River

NOVEMBER 2, 2023

Some are standard, offering the basic services you need to ensure traffic routing and low latency, while others offer premium services like advanced security capabilities. Capacity CommitmentCommitting to a certain capacity for CDNs saves money by giving you a discounted rate on CDN bandwidth and storage.

Infrastructure 52

Infrastructure Traffic Cache Strategy 52

Percona

JULY 17, 2023

Instead of the table-based structure of relational databases, MongoDB stores data in documents and collections, a design for handling large amounts of unstructured data and for real-time web applications. More specifically, DBAs and developers like that MongoDB stores data in JSON-like documents with optional schemas.

Open Source 79

Open Source Database Scalability Software 79

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. That matters if your store reads data in (multi-key) blocks. For UDB, many read requests for popular data will be handled by the upper cache tiers and so never hit RocksDB.

Benchmarking 59

Benchmarking Storage Cache Open Source 59

The Morning Paper

FEBRUARY 23, 2020

The Web provides decentralised publishing and direct access to unstructured data ( searching / querying that data has turned out to be a pretty centralised affair in practice though). AnyLog wants to do for structured (relational) data what the Web has done for unstructured data, with coordinators playing the role of search engines.

Blockchain 94

Blockchain Internet Internet IoT 94

Highly Scalable

AUGUST 20, 2013

The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. This system has been designed to supplement and succeed the existing Hadoop-based system that had too high latency of data processing and too high maintenance costs.

Big Data 154

Big Data Processing Lambda Database 154

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . In-Memory Data Grids for Fast-Changing Data. For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . In-Memory Data Grids for Fast-Changing Data. For more than fifteen years, ScaleOut StateServer® has demonstrated technology leadership as an in-memory data grid (IMDG) and distributed cache.

Analytics 52

Analytics Airlines Cache Scalability 52