Scalegrid

FEBRUARY 8, 2024

At its core, a distributed storage system comprises three main components: a controller for managing the system’s operations, an internal datastore where information is held, and databases geared towards ensuring scalability, partitioning capabilities, and high availability for all types of data.

Storage 130

Storage Systems Big Data Azure 130

Scalegrid

JANUARY 8, 2024

Key Takeaways AI integration in cloud computing increases operational efficiency by automating processes, optimizing resource allocation, and improving scalability, leading to cost savings and allowing IT teams to concentrate on strategic initiatives. These services are tailored to meet various business requirements.

Artificial Intelligence 147

Artificial Intelligence Cloud Scalability Analytics 147

Dynatrace

APRIL 10, 2023

Kiran Bollampally, site reliability and digital analytics lead for ecommerce at Tractor Supply Co., shifted most of its ecommerce and enterprise analytics workloads to Kubernetes-managed software containers running in Microsoft Azure. “At one point, we saw a process that was causing a lot of CPU contention.

Cloud 171

Cloud Ecommerce Performance Retail 171

Dynatrace

JANUARY 31, 2024

The RAG process begins by summarizing and converting user prompts into queries that are sent to a search platform that uses semantic similarities to find relevant data in vector databases, semantic caches, or other online data sources. Observing AI models Running AI models at scale can be resource-intensive.

Cache 205

Cache Azure Infrastructure Monitoring 205

Dynatrace

FEBRUARY 12, 2024

At the 2024 Dynatrace Perform conference in Las Vegas, Michael Winkler, senior principal product management at Dynatrace, ran a technical session exploring just some of the many ways in which Dynatrace helps to automate the processes around development, releases, and operation.

Engineering 182

Engineering Development Infrastructure Cloud 182

ScaleOut Software

AUGUST 5, 2020

And how are they different from streaming pipelines like Azure Stream Analytics and Apache Flink/Beam? What Problems Does Streaming Analytics Solve? To understand why we need real-time digital twins for streaming analytics, we first need to look at what problems are tackled by popular streaming platforms.

Analytics 69

Analytics Azure Processing Speed 69

Dynatrace

FEBRUARY 8, 2021

Leveraging cloud-native technologies like Kubernetes or Red Hat OpenShift in multicloud ecosystems across Amazon Web Services (AWS) , Microsoft Azure, and Google Cloud Platform (GCP) for faster digital transformation introduces a whole host of challenges. Dynatrace news. Logs provide information you can’t find anywhere else.

Cloud 260

Cloud Azure Analytics AWS 260

High Scalability

JANUARY 11, 2022

We will use a graph database such as Neo4j to store the information. Additionally, we can use columnar databases like Cassandra to store information like user feeds, activities, and counters. There are two major processes which gets executed when a user posts a photo on Instagram. System Components. Component Design. API Design.

Design 334

Design Media Storage Logistics 334

Scalegrid

JANUARY 12, 2024

Simply put, it’s the set of computational tasks that cloud systems perform, such as hosting databases, enabling collaboration tools, or running compute-intensive algorithms. In the realm of cloud-based business operations, there is an increasing dependence on complex information processing patterns. What is workload in cloud computing?

Cloud 130

Cloud Virtualization Storage Efficiency 130

Dynatrace

APRIL 21, 2022

If you still use the legacy version of Log Monitoring ( Log Monitoring v1 ), the Log Monitoring v1 documentation is still available, but we strongly encourage you to switch to the latest Dynatrace Log Monitoring version and gain direct access to the log content of all your mission-critical processes. Kubernetes/OpenShift workload/pod details.

Azure 216

Azure Metrics AWS Monitoring 216

Scalegrid

MARCH 14, 2024

Defining Hybrid Cloud Strategy The decision-making process about where to situate data and applications is vital to any hybrid cloud solution. A pivotal element of any hybrid cloud strategy is adhering to regulatory requirements and compliance standards specific to an industry.

Strategy 130

Strategy Cloud Artificial Intelligence Infrastructure 130

Dynatrace

JANUARY 20, 2022

Azure supporting services (Synapse Analytics). DL/I segment name for DL/I databases. WeThe Detected processes page has been clarified. The trace list now correctly supports sorting on the number of database calls. (APM-340223). Time aggregation corrected for `GC time` chart on process group instance page. (APM-343594).

Lambda 180

Lambda AWS Metrics Azure 180

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. This leads us to the process page of our specific Apache instance. And that’s where Dynatrace OneAgent comes in.

Metrics 171

Metrics Monitoring Database Network 171

Dynatrace

DECEMBER 2, 2021

Settings > Anomaly detection > Database services. New analytics view for message queues. Azure VMs that are monitoring candidates are now labeled “no OneAgent” on the Azure region and scale set pages. (APM-323431). Corrected issue with process group monitoring overrides. Dynatrace API.

Lambda 193

Lambda Azure Metrics Monitoring 193

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 59

Analytics Social Media Ecommerce Serverless 59

Scalegrid

OCTOBER 7, 2019

As this open source database continues to pull new users from expensive commercial database management systems like Oracle, DB2 and SQL Server, organizations are adopting new approaches and evolving their own to maintain the exceptional performance of their SQL deployments. PostgreSQL popularity is skyrocketing in the enterprise space.

Strategy 182

Strategy Cloud Java Open Source 182

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. This simplifies the installation process and ensures portability across operating systems.

IoT 52

IoT Azure Analytics Healthcare 52

ScaleOut Software

JANUARY 31, 2020

Consider the typical, conventional streaming analytics pipeline available on popular cloud platforms: A conventional pipeline combines telemetry from all data sources into a single stream which is queried by the user’s streaming analytics application. It’s simply not practical to create a unique query tailored for each data source.

Analytics 52

Analytics Social Media Serverless Cloud 52

Dynatrace

NOVEMBER 10, 2022

Cloud-native architecture is a structural approach to planning and implementing an environment for software development and deployment that uses resources and processes common with public clouds like Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Microservices. The principles of cloud-native architecture.

Cloud 163

Cloud Architecture Serverless Infrastructure 163

Dynatrace

JANUARY 5, 2022

In white-box testing, we combine open-source load testing tools such as JMeter with Dynatrace’s observability and analytics capabilities. As switching or integrating new tools in an automation process is always a lot of work, we expect Keptn to help us lower the automation efforts in our current Jenkins pipelines.

Testing 217

Testing Open Source Metrics Infrastructure 217

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

Scalegrid

JUNE 11, 2019

Ready to transition from a commercial database to open source, and want to know which databases are most popular in 2019? Wondering whether an on-premise vs. public cloud vs. hybrid cloud infrastructure is best for your database strategy? Polyglot Persistence Trends : Number of Databases Used & Top Combinations.

Open Source 55

Open Source Database Cloud Infrastructure 55

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications in operational environments such as these require. With the real-time digital twin model, the next generation of streaming analytics has arrived.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

Traditional platforms for streaming analytics don’t offer the combination of granular data tracking and real-time aggregate analysis that logistics applications such as these require. It’s not enough to just pick out interesting events from an aggregated data stream and then send them to a database for offline analysis using Spark.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

ScaleOut Software

MAY 19, 2020

Today ScaleOut Software announces the release of its ground-breaking cloud service for streaming analytics using the real-time digital twin model. Traditional platforms for streaming analytics attempt to look at the entire telemetry pipeline using techniques such as SQL query to uncover and act on patterns of interest.

Logistics 52

Logistics IoT Analytics Azure 52

Dynatrace

JUNE 1, 2021

However, with today’s highly connected digital world, monitoring use cases expand to the services, processes, hosts, logs, networks, and of course, end-users that access these applications — including a company’s customers and employees. User experience and business analytics. What does APM stand for?

Monitoring 149

Monitoring Mobile Social Media Artificial Intelligence 149

ScaleOut Software

JUNE 22, 2020

When first introduced, distributed caching offered a breakthrough for applications by storing fast-changing data in memory on a server cluster for consistently fast response times, while simultaneously offloading database servers that would otherwise become bottlenecked.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

ScaleOut Software

JUNE 22, 2020

When first introduced, distributed caching offered a breakthrough for applications by storing fast-changing data in memory on a server cluster for consistently fast response times, while simultaneously offloading database servers that would otherwise become bottlenecked.

Ecommerce 52

Ecommerce Cache Scalability IoT 52

Dynatrace

MAY 28, 2020

While Google’s SRE Handbook mostly focuses on the production use case for SLIs/SLOs, Keptn is “Shifting-Left” this approach and using SLIs/SLOs to enforce Quality Gates as part of your progressive delivery process. This will enable deep monitoring of those Java,NET, Node, processes as well as your web servers.

Engineering 192

Engineering Performance Metrics Best Practices 192

Scalegrid

JANUARY 3, 2020

Monitoring your MySQL database performance in real-time helps you immediately identify problems and other factors that could be causing issues now or in the future. It’s also a good way to determine which components of the database can be enhanced or optimized to increase your efficiency and performance.

Monitoring 164

Monitoring Metrics Servers Database 164

SQL Server According to Bob

FEBRUARY 15, 2018

Microsoft engineering is actually sending quite a few folks over the Atlantic to come talk about SQL Server 2017, SQL Server on Linux, GDPR, Performance, Security, Azure Data Lake, Azure SQL Database, Azure SQL Data Warehouse, and Azure CosmosDB. SELECT * FROM Azure Cosmos DB – Andrew Liu.

Engineering 40

Engineering Azure Best Practices Servers 40

Dynatrace

SEPTEMBER 17, 2019

Cluster and container Log Analytics. In order to filter these dashboards by tenant all they need is a Dynatrace Management Zone , which is based on meta data extracted by Dynatrace from e.g. k8s tags, container labels or process environment variables. 3 Log Analytics. Full-stack observability. End-to-end code-level tracing.

AWS 128

AWS Monitoring Ecommerce Lambda 128

Dotcom-Montior

OCTOBER 19, 2021

In the past, this process would have taken an entire team of individuals. It also can integrate with cloud-based providers, like Amazon, Google Cloud Platform, Azure, and others. Monitoring & Analytics. Grafana is an open-source analytics and monitoring tools used by SREs to visualize data and metrics at-a-glance.

Engineering 86

Engineering Open Source Programming Monitoring 86

The Morning Paper

SEPTEMBER 19, 2019

MongoDB is an important database, and this paper explains the tunable (per-operation) consistency models that MongoDB provides and how they are implemented under the covers. Microsoft have a paper describing their new recovery mechanism in Azure SQL Database , the key feature being that it can recovery in constant time.

Blockchain 46

Blockchain Hardware Google Analytics 46

SQL Server According to Bob

OCTOBER 26, 2017

In-database Machine Learning in SQL Server 2017. SQL Server 2017: Fast, faster, and the fastest database everywhere you need it. Enhancing query performance with Adaptive Query Processing in SQL Server 2017. Microsoft Data Platform – SQL Server 2017 and Azure Data Services. Microsoft for the Modern Data Estate.

Servers 40

Servers Azure Open Source Database 40