DZone

JULY 6, 2020

TiDB is an open-source, distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. Ideally, a TiDB cluster should always be efficient and problem-free. It should be stable, load-balanced, and have a reliable rate of queries per second (QPS).

Open Source 130

Open Source Latency Traffic Analytics 130

Scalegrid

DECEMBER 14, 2023

For example, your payment history might be on one database cluster and your analytics records on another cluster. If your analytics server is down, then each operation will wait for a default of 30 seconds before failing (which may or may not be what you want). Careful consideration must be given before making changes.

Java 130

Java Network Servers Database 130

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. In-Memory Data Grids for Fast-Changing Data.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . By transparently distributing stored objects across a cluster of servers (physical or virtual), it automatically scales performance for fast-growing workloads and maintains consistently low access latency. In-Memory Data Grids for Fast-Changing Data.

Analytics 52

Analytics Airlines Cache Scalability 52

Dynatrace

APRIL 25, 2023

Higher latency and cold start issues due to the initialization time of the functions. Observability challenges in serverless applications can be therefore categorized into: Data collection : how to collect metrics, logs and traces from serverless functions efficiently, reliably, and consistently?

Serverless 207

Serverless Lambda Azure AWS 207

Percona

JUNE 22, 2023

We will also discuss related configuration variables to consider that can impact these KPIs, helping you gain a comprehensive understanding of your MySQL server’s performance and efficiency. Query performance Query performance is a key performance indicator (KPI) in MySQL, as it measures the efficiency and speed of query execution.

Performance 104

Performance Monitoring Traffic Database 104

Dynatrace

APRIL 26, 2022

Digital experience monitoring enables companies to respond to issues more efficiently in real time, and, through enrichment with the right business data, understand how end-user experience of their digital products significantly affects business key performance indicators (KPIs).

Monitoring 203

Monitoring Social Media IoT Metrics 203

Dynatrace

DECEMBER 15, 2022

This includes response time, accuracy, speed, throughput, uptime, CPU utilization, and latency. Adding application security to development and operations workflows increases efficiency. This is the number of failures that affect users’ ability to use an application by the total time in service. Performance.

Artificial Intelligence 202

Artificial Intelligence DevOps Hardware Virtualization 202

Dynatrace

MAY 5, 2021

For example, improving latency by as little as 0.1 latency is the number one reason consumers abandon mobile sites. ” Data from the build process feeds impactful analytics from Davis AI to detect the precise root cause if software fails to meet specific benchmarks. Meanwhile, in the U.S.,

Benchmarking 183

Benchmarking Latency Speed Software 183

Percona

NOVEMBER 2, 2023

Inside, you will learn: Why you should upgrade MongoDB Staying with outdated MongoDB versions can expose you to critical security vulnerabilities, suboptimal performance, and missed opportunities for efficiency. Introduction of clustered collections for optimized analytical queries. In MongoDB 6.x:

Best Practices 86

Best Practices Hardware Tuning Scalability 86

Dynatrace

FEBRUARY 2, 2022

service availability with <50ms latency for an application with no revenue impact. Tailoring SLOs in this way ensures that you’re spending resources making sure that SLOs are met, used efficiently, driving customer value, and helping Developers improve their QA and resolution processes.

DevOps 196

DevOps Metrics Best Practices Latency 196

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

The Netflix TechBlog

OCTOBER 19, 2020

If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls. However, having a scalable stream processing platform doesn’t help much if you can’t store data in a cost efficient manner.

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

Dynatrace

JULY 6, 2020

Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics. With our brand new Azure Front Door page, you get immediate insights into the number of served client requests, latency, and back-end health, so you always have a clear picture of the metrics that really matter.

Azure 148

Azure Cloud Big Data Virtualization 148

Dotcom-Montior

OCTOBER 6, 2021

Site reliability engineers are focused with creating scalable and reliable software systems, so this also includes ensuring that development work is efficient and reliable, so when the finished product is ready for production, there are no surprises. that are required to keep the software deployments live are running efficiently.

Engineering 67

Engineering DevOps Monitoring Google 67

Dotcom-Montior

DECEMBER 8, 2021

By ITIL definition, the service desk may take the form of incident resolution or service requests, but whatever the case, the primary goal of the service desk to provide quick and efficient service. This helps to improve efficiency and ensures that information is consistent, up-to-date, and available. Problem Management.

Social Media 90

Social Media Monitoring Latency DevOps 90

Scalegrid

DECEMBER 21, 2023

Identifying key Redis® metrics such as latency, CPU usage, and memory metrics is crucial for effective Redis monitoring. To monitor Redis® instances effectively, collect Redis metrics focusing on cache hit ratio, memory allocated, and latency threshold.

Strategy 130

Strategy Monitoring Latency DevOps 130

The Morning Paper

SEPTEMBER 8, 2019

I’ve been excited about the potential for approximate query processing in analytic clusters for some time, and this paper describes its use at scale in production. In total, the clusters store a few exabytes of data and are primarily responsible for all of the batch analytics at Microsoft. VLDB’19. Approximate query support.

Big Data 57

Big Data Analytics Latency Azure 57

Abhishek Tiwari

JULY 12, 2018

It can be used to power new analytics, insight, and product features. It can be used to power new analytics, insight, and product features. Processing latency is minimum If only you can infinitely scale your data pipeline, processing latency can be guaranteed to be minimum, but we know for sure that is not true.

Latency 63

Latency Analytics Scalability Engineering 63

VoltDB

JUNE 29, 2017

Most existing adtech infrastructure simply can not achieve the required latency. VoltDB provides the necessary technology to achieve the latency required by header bidding. DSPs and SSPs need to filter out low-value data quickly and cost-efficiently to free up capacity. Another adtech infrastructure problem is capacity.

Performance 40

Performance Hardware Latency Infrastructure 40

VoltDB

JUNE 29, 2017

Most existing adtech infrastructure simply can not achieve the required latency. VoltDB provides the necessary technology to achieve the latency required by header bidding. DSPs and SSPs need to filter out low-value data quickly and cost-efficiently to free up capacity. Another adtech infrastructure problem is capacity.

Performance 40

Performance Hardware Latency Infrastructure 40

Scalegrid

FEBRUARY 8, 2024

Durability Availability Fault tolerance These combined outcomes help minimize latency experienced by clients spread across different geographical regions. This makes adopting such sophisticated multi-node-based arrangements exceedingly advantageous from both operational efficiency and financial viewpoints.

Storage 130

Storage Systems Big Data Azure 130

Scalegrid

MARCH 28, 2024

Snapshots provide point-in-time captures of the dataset, which are efficient for recovery on startup. Memcached shines in scenarios where a simple, fast, and efficient caching solution is required without data persistence. Memory Efficiency Compared When it comes to memory efficiency, Redis and Memcached have different strengths.

Cache 130

Cache Storage Scalability Architecture 130

Scalegrid

MARCH 14, 2024

In practice, a hybrid cloud operates by melding resources and services from multiple computing environments, which necessitates effective coordination, orchestration, and integration to work efficiently. Tailoring resource allocation efficiently ensures faster application performance in alignment with organizational demands.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dean Hume

APRIL 24, 2018

Without effective caching on the client, the server will see an increase in workload, more CPU usage and ultimately increased latency for the end user. Processors and memory consume the most power on the server, followed by the power supply efficiency loss. CPU Utilization and Power Consumption (Source: Blackburn 2008).

Energy 40

Energy Cache Traffic Website 40

Dean Hume

APRIL 24, 2018

Without effective caching on the client, the server will see an increase in workload, more CPU usage and ultimately increased latency for the end user. Processors and memory consume the most power on the server, followed by the power supply efficiency loss. CPU Utilization and Power Consumption (Source: Blackburn 2008).

Energy 40

Energy Cache Traffic Website 40

Dean Hume

APRIL 24, 2018

Without effective caching on the client, the server will see an increase in workload, more CPU usage and ultimately increased latency for the end user. Processors and memory consume the most power on the server, followed by the power supply efficiency loss. CPU Utilization and Power Consumption (Source: Blackburn 2008).

Energy 40

Energy Cache Traffic Website 40

The Morning Paper

SEPTEMBER 10, 2019

Procella: unifying serving and analytical data at YouTube Chattopadhyay et al., When each of those use cases is powered by a dedicated back-end, investments in better performance, improved scalability and efficiency etc. Oh, and in additional to low latency, “ we require access to fresh data.” VLDB’19.

Analytics 75

Analytics Latency Cache Google 75

Highly Scalable

AUGUST 20, 2013

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. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. Efficient lineage tracking is not a trivial problem.

Big Data 154

Big Data Processing Lambda Database 154

The Netflix TechBlog

JANUARY 10, 2024

This architecture shift greatly reduced the processing latency and increased system resiliency. We expanded pipeline support to serve our studio/content-development use cases, which had different latency and resiliency requirements as compared to the traditional streaming use case. divide the input video into small chunks 2.

Processing 229

Processing Media Latency Innovation 229

Dynatrace

OCTOBER 4, 2022

While data lakes and data warehousing architectures are commonly used modes for storing and analyzing data, a data lakehouse is an efficient third way to store and analyze data that unifies the two architectures while preserving the benefits of both. Data lakehouses deliver the query response with minimal latency. Reduced redundancy.

Artificial Intelligence 209

Artificial Intelligence Storage Analytics Government 209

Dynatrace

JULY 24, 2023

In the world of DevOps and SRE, DevOps automation answers the undeniable need for efficiency and scalability. This evolution in automation, referred to as answer-driven automation, empowers teams to address complex issues in real time, optimize workflows, and enhance overall operational efficiency.

DevOps 220

DevOps Traffic Efficiency Servers 220

Scalegrid

JANUARY 12, 2024

This article analyzes cloud workloads, delving into their forms, functions, and how they influence the cost and efficiency of your cloud infrastructure. The public cloud provides flexibility and cost efficiency through utilizing a provider’s resources. These include on-premises data centers which offer specific business benefits.

Cloud 130

Cloud Virtualization Storage Efficiency 130

The Netflix TechBlog

JULY 26, 2021

Operational Reporting is a reporting paradigm specialized in covering high-resolution, low-latency data sets, serving detailed day-to-day activities¹ and processes of a business domain. Operational Reporting Pipeline Example Iceberg Sink Apache Iceberg is an open source table format for huge analytics datasets. tactical) in nature.

Big Data 253

Big Data Government Analytics Processing 253

Adrian Cockcroft

MAY 6, 2023

I don’t advocate “Serverless Only”, and I recommended that if you need sustained high traffic, low latency and higher efficiency, then you should re-implement your rapid prototype as a continuously running autoscaled container, as part of a larger serverless event driven architecture, which is what they did.

Serverless 145

Serverless Lambda Best Practices Traffic 145

The Netflix TechBlog

OCTOBER 27, 2020

Data scientists and engineers collect this data from our subscribers and videos, and implement data analytics models to discover customer behaviour with the goal of maximizing user joy. The data warehouse is not designed to serve point requests from microservices with low latency. Moving data with Bulldozer at Netflix.

Latency 243

Latency Storage Big Data Tuning 243

The Netflix TechBlog

SEPTEMBER 2, 2020

Edgar helps Netflix teams troubleshoot distributed systems efficiently with the help of a summarized presentation of request tracing, logs, analysis, and metadata. In one request hitting just ten services, there might be ten different analytics dashboards and ten different log stores. What is Edgar?

Latency 296

Latency Transportation Engineering Traffic 296