Dynatrace

JANUARY 31, 2024

Data observability is crucial to analytics and automation, as business decisions and actions depend on data quality. Davis AI, Grail, and data observability By grouping common data observability issues into industry-standard pillars, we can provide tangible examples and showcase current capabilities.

DevOps 194

DevOps Analytics Airlines Metrics 194

Dynatrace

SEPTEMBER 13, 2023

This is where unified observability and Dynatrace Automations can help by leveraging causal AI and analytics to drive intelligent automation across your multicloud ecosystem. For example, optimizing resource utilization for greater scale and lower cost and driving insights to increase adoption of cloud-native serverless services.

AWS 246

AWS Efficiency Azure Cloud 246

Dynatrace

SEPTEMBER 18, 2020

High latency or lack of responses. You receive an alert message from Dynatrace (your infrastructure observability hub) letting you know that the average response latency of all deployed APIs has tripled. This increase is clearly correlated with the increased response latencies. Soaring number of active connections.

Infrastructure 191

Infrastructure Latency Metrics Analytics 191

High Scalability

JANUARY 11, 2022

When a user requests for feed then there will be two parallel threads involved in fetching the user feeds to optimize for latency. We can use cloud technologies such as Amazon Kinesis or Azure Stream Analytics for collecting, processing, and analyzing real-time, streaming data to get timely insights and react quickly to new information(e.g.

Design 334

Design Media Storage Logistics 334

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

JANUARY 31, 2024

For example, a Stanford University and UC Berkeley team noted in a research study that ChatGPT behavior deteriorates over time. Using the example of a chatbot, once the user submits a natural language prompt, RAG summarizes that prompt using semantic data. Consequently, AI model drift and hallucinations emerge as primary concerns.

Cache 204

Cache Azure Infrastructure Monitoring 204

Dynatrace

APRIL 26, 2022

STM generates traffic that replicates the typical path or behavior of a user on a network to measure performance for example, response times, availability, packet loss, latency, jitter, and other variables). How automatic and intelligent AIOps makes DEM and business observability possible.

Monitoring 203

Monitoring Social Media IoT Metrics 203

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).

Java 130

Java Network Servers Database 130

Dynatrace

APRIL 25, 2023

For example, to handle traffic spikes and pay only for what they use. Higher latency and cold start issues due to the initialization time of the functions. With Davis AI exploratory analytics , Dynatrace gives you a helping hand to understand correlations between anomalies across all the telemetry.

Serverless 207

Serverless Lambda Azure AWS 207

Dynatrace

JULY 24, 2023

For example, consider an e-commerce website that automatically sends personalized discount codes to customers who abandon their shopping carts. Let’s examine a few examples of answer-driven automation using AI and context. DevOps automation example #2: Threat detection and response Let’s build on the previous example.

DevOps 220

DevOps Traffic Efficiency Servers 220

Scalegrid

FEBRUARY 8, 2024

Durability Availability Fault tolerance These combined outcomes help minimize latency experienced by clients spread across different geographical regions. These distributed storage services also play a pivotal role in big data and analytics operations.

Storage 130

Storage Systems Big Data Azure 130

Dynatrace

MAY 17, 2023

The next level of observability: OneAgent In the first two parts of our series, we used OpenTelemetry to manually instrument our application and send the telemetry data straight to the Dynatrace analytics back end. Let’s take our previous screenshot as an example. Yet, we have two entries for these two services in our list.

Metrics 171

Metrics Monitoring Database Network 171

Dynatrace

FEBRUARY 2, 2022

For example, the IT team of a bank wants to ensure that for a trailing 30-day period there is 99.9% service availability with <50ms latency for an application with no revenue impact. Let’s take service availability for example. This can create an unnecessary distraction and steal time away from critical tasks.

DevOps 196

DevOps Metrics Best Practices Latency 196

Dynatrace

OCTOBER 4, 2021

For example, some developers may be using an old version of an API that will soon be deprecated. When choosing an API monitoring tool, keep in mind that not all have the same breadth of functionality or depth of analytic capabilities. This can provide a better understanding of areas that need improvement or updating.

Monitoring 178

Monitoring Latency Metrics Availability 178

Scalegrid

JANUARY 12, 2024

Various forms can take shape when discussing workloads within the realm of cloud computing environments – examples include order management databases, collaboration tools, videoconferencing systems, virtual desktops, and disaster recovery mechanisms. What is an example of a workload?

Cloud 130

Cloud Virtualization Storage Efficiency 130

Highly Scalable

MAY 1, 2012

Statistical analysis and mining of huge multi-terabyte data sets is a common task nowadays, especially in the areas like web analytics and Internet advertising. This approach often leads to heavyweight high-latency analytical processes and poor applicability to realtime use cases.

Analytics 191

Analytics Traffic Big Data Efficiency 191

All Things Distributed

OCTOBER 16, 2019

There are places so remote, so harsh that humans can't safely explore them (for example, hundreds of miles below the earth, areas that experience extreme temperatures, or on other planets). Here's a few examples: IoT sensors in a factory can monitor and predict equipment failure before an accident.

IoT 126

IoT Healthcare Internet Internet 126

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

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 182

Benchmarking Latency Speed Software 182

Percona

JUNE 22, 2023

Let’s dive in and learn how (and what) to effectively monitor MySQL performance, along with examples from PMM, by understanding the critical KPIs to watch for. This is not an exhaustive list but an example of what we can watch for.

Performance 105

Performance Monitoring Traffic Database 105

Dynatrace

DECEMBER 22, 2019

Amazon Kinesis Data Analytics. You can observe the metrics across service instances split by region (in this example, API Gateways in us-east-1 and us-east-2 ). Metrics for each service instance are presented in detailed charts—see the example for ECS below. Amazon Elastic File System (EFS). Amazon EMR. Amazon Redshift.

AWS 136

AWS Metrics IoT Storage 136

Dynatrace

DECEMBER 22, 2019

Amazon Kinesis Data Analytics. You can observe the metrics across service instances split by region (in this example, API Gateways in us-east-1 and us-east-2 ). Metrics for each service instance are presented in detailed charts—see the example for ECS below. Amazon Elastic File System (EFS). Amazon EMR. Amazon Redshift.

AWS 133

AWS Metrics IoT Storage 133

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Analytics and insights have always taken a back seat to the first two priorities – accurate data processing and billing. Does this affect our analytics strategy? The answer: Absolutely! downgrading the streaming rate on video).

Analytics 40

Analytics Strategy Network Games 40

VoltDB

JUNE 9, 2017

Historically, telco analytics have been limited and difficult. Analytics and insights have always taken a back seat to the first two priorities – accurate data processing and billing. Does this affect our analytics strategy? The answer: Absolutely! downgrading the streaming rate on video).

Analytics 40

Analytics Strategy Network Games 40

Dynatrace

DECEMBER 2, 2021

For example, an SLA between a web host provider and customer can guarantee 99.95% uptime for all web services of a company over a year. For example, if the SLA for a website is 99.95% uptime, its corresponding SLO could be 99.95% availability of the login services. For example, if your SLO guarantees 99.5% What are SLOs?

Metrics 191

Metrics Best Practices DevOps Infrastructure 191

The Netflix TechBlog

MARCH 10, 2023

Production Use Cases Real-Time APIs (backed by the Cassandra database) for asset metadata access don’t fit analytics use cases by data science or machine learning teams. Following is the example of tables primary and clustering keys defined: Figure 2. Some of the common supported data reprocessing use cases are listed below.

Media 237

Media Traffic Processing Design 237

ScaleOut Software

APRIL 6, 2021

With the ScaleOut Digital Twin Streaming Service , an Azure-hosted cloud service, ScaleOut Software introduced breakthrough capabilities for streaming analytics using the real-time digital twin concept. Scaleout StreamServer® DT was created to meet this need.

IoT 52

IoT Azure Analytics Healthcare 52

Dynatrace

NOVEMBER 3, 2021

For example, we can actively watch a single metric for changes that indicate a problem — this is monitoring. For example, when monitoring a database, you’ll want to know about any latency when writing data to a disk or average query response time.

Monitoring 220

Monitoring Metrics DevOps Scalability 220

Dynatrace

JUNE 25, 2021

Already in the 2000s, service-oriented architectures (SOA) became popular, and operations teams discovered the need to understand how transactions traverse through all tiers and how these tiers contributed to the execution time and latency. Let me give you an example. In both cases, a broken trace will be the result. What’s next.

Open Source 199

Open Source Monitoring Google Systems 199

Smashing Magazine

OCTOBER 31, 2023

For example, the data is pretty slow to update, refreshing every 28 days, meaning it is not the same as real-time monitoring. This data is distinct from CrUX because it’s collected directly by the website owner by installing an analytics snippet on their website. But it comes with caveats.

Speed 99

Speed Google Website Metrics 99

ACM Sigarch

MARCH 18, 2019

Analytic models—including simple ones like Amdahl’s Law —represent a third, often underused, evaluation method that can provide insight for both practice and research, albeit with less accuracy. How many buffers are needed to track pending requests as a function of needed bandwidth and expected latency? Answered in Part 2.).

Systems 60

Systems Latency Performance Analytics 60

The Netflix TechBlog

OCTOBER 19, 2020

a Netflix member via Twitter This is an example of a question our on-call engineers need to answer to help resolve a member issue?—?which Using simple lookup indices in Cassandra gives us the ability to maintain acceptable read latencies while doing heavy writes. which is difficult when troubleshooting distributed systems.

Infrastructure 233

Infrastructure Transportation Storage Open Source 233

Speed Curve

MARCH 11, 2024

But we also approach each new metric with an analytical eye. One of the biggest culprits: latency, which is typically worse on mobile. Before we go any further, you might find it interesting to learn a bit more about First Input Delay (FID), the interactivity metric that preceded INP in Core Web Vitals, and why it was deprecated.

Mobile 81

Mobile Google Metrics Monitoring 81

Dynatrace

JULY 6, 2020

Let’s look at the Azure DB for MariaDB overview as an example. Azure HDInsight supports a broad range of use cases including data warehousing, machine learning, and IoT analytics. Database-service views provide all the metrics you need to set up high-performance database services. Get a comprehensive view of your batch jobs.

Azure 147

Azure Cloud Big Data Virtualization 147

Smashing Magazine

MARCH 25, 2021

For example, a budget can help them decide if a page should contain five images — or three images and one video — and still remain within the planned limits. For example, can you replace a paragraph of text and the associated images with a short video? Large preview ). Appeal Of Videos. Deliver through multiple CDNs.

Media 118

Media Performance Mobile Latency 118

Dotcom-Montior

NOVEMBER 24, 2021

Ok, so maybe that is an oversimplified example, but you get the point. For example, you can think of a cell phone network as a type of distributed system, consisting of a network of internet-connected devices that share resources workload. Blockchain is a good example of this. Awesome, everything is running as expected.

Systems 74

Systems Monitoring Hardware Network 74