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Managing PostgreSQL® High Availability – Part I: PostgreSQL Automatic Failover

Scalegrid

Managing High Availability (HA) in your PostgreSQL hosting is very important to ensuring your database deployment clusters maintain exceptional uptime and strong operational performance so your data is always available to your application. Effective management of failover and switchover operations is crucial for high availability.

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Dynatrace extends Synthetic Monitoring capabilities with Network Availability Monitors to validate the availability of infrastructure and services

Dynatrace

As HTTP and browser monitors cover the application level of the ISO /OSI model , successful executions of synthetic tests indicate that availability and performance meet the expected thresholds of your entire technological stack. Our script, available on GitHub , provides details. Are the corresponding services running on those hosts?

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Business Flow: Why IT operations teams should monitor business processes

Dynatrace

The business process observability challenge Increasingly dynamic business conditions demand business agility; reacting to a supply chain disruption and optimizing order fulfillment are simple but illustrative examples. Most business processes are not monitored. First and foremost, it’s a data problem.

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Batch Processing for Data Integration

DZone

Among the spectrum of methodologies available for this task, batch processing is often considered an old guard, especially with the advent of real-time and event-based processing technologies. However, it would be a mistake to dismiss batch processing as an antiquated approach.

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Don’t just react: How executives can predict and prevent outages to maximize availability

Dynatrace

The end goal, of course, is to optimize the availability of organizations’ software. Dynatrace is widely recognized for its AI capabilities’ ability to predict and prevent issues, and automatically identify root causes, maximizing availability.

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Leverage logs for an end-to-end view of your business processes via Dynatrace OpenPipeline

Dynatrace

Unrealized optimization potential of business processes due to monitoring gaps Imagine a retail company facing gaps in its business process monitoring due to disparate data sources. Due to separated systems that handle different parts of the process, the view of the process is fragmented.

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2. Diving Deeper into Psyberg: Stateless vs Stateful Data Processing

The Netflix TechBlog

By Abhinaya Shetty , Bharath Mummadisetty In the inaugural blog post of this series, we introduced you to the state of our pipelines before Psyberg and the challenges with incremental processing that led us to create the Psyberg framework within Netflix’s Membership and Finance data engineering team.