Listen to the recorded webinar here: http://info.appdynamics.com/webinars.html?eventid=1022540&key=7E90DB53838CC4874814EACA25AB9619
How to perform quick and dirty performance analysis and use technology like Lumira to visualise the output.
The document provides an overview of best practices for software delivery, including: - Components like distribution packages, bundles, distribution servers, and rollout projects. - Delivery methods like self-organizing multicast where machines select a multicast domain representative to distribute files. - Settings for urgency, efficiency, and agent settings to control delivery. - Architectures using sources, replicators, and preferred servers to store and replicate content across sites.
A lot of businesses that never before considered themselves as “technology companies” are now faced with digital modernization imperatives that force them to rethink their application and infrastructure architecture. On the path to becoming a digital, on-demand provider, development speed is the ultimate competitive advantage. https://info.lightbend.com/webinar-java-ee-to-cloud-modernization-register.html
This document discusses Splunk's developer platform and resources for building applications on Splunk. It provides an overview of empowering developers through application intelligence, building Splunk apps, and integrating and extending Splunk. The document discusses Splunk for application development and challenges such as lack of visibility and limited insights. It describes gaining end-to-end visibility across development tools using Splunk and pushing better code using analytics in Splunk. Resources mentioned include Splunk's developer license, tutorials on their developer website, GitHub, and blogs.
For enterprises, it's rarely a single function causing your OSS problem, it's a combination of architecture, packages, or networks. Using three real-world examples, these slides, from our recent webinar, walk through identifying the infrastructure needs, the technology stack selection process, and the final architected solution for each environment (e-commerce, PaaS, and HPC machine learning.)
The development of clustered JIRA was a complex project spanning more than a year, and resulting in significant changes to core components of JIRA. We will discuss some of the changes made to Lucene index architecture, caching and scheduling, and the migration of jira.atlassian.com as the very first production clustered JIRA.
This document discusses 8 cloud design patterns: External Configuration, Cache Aside, Federated Identity, Valet Key, Gatekeeper, Circuit Breaker, Retry, and Strangler. It provides an overview of each pattern, including what problem it addresses, when to use it, considerations, and examples of cloud offerings that implement each pattern. It aims to help developers understand and apply common best practices for cloud application design.
This document discusses the importance of implementing FinOps practices to optimize cloud spending. FinOps advocates for collaborative work between development, operations, and finance teams to provide transparency into infrastructure costs, optimize resource utilization, and balance speed of development with cloud efficiency. The document outlines why FinOps is needed due to rising cloud bills and lack of visibility. It proposes implementing tagging, metrics, and recommendation systems to allocate costs and identify optimization opportunities in a decentralized manner. FinOps requires cultural and process changes, as well as open source tooling, to establish a collaborative cost management approach.
[About This Webinar] Streaming data systems, so called Fast Data, promise accelerated access to information, leading to new innovations and competitive advantages. These systems, however, aren’t just faster versions of Big Data; they force architecture changes to meet new demands for reliability and dynamic scalability, more like microservices. This means new challenges for your organization. Whereas a batch job might run for hours, a stream processing application might run for weeks or months. This raises the bar for making these systems resilient against traffic spikes, hardware and network failures, and so forth. The good news is that there is a strong history of facing these demands in the world of microservices. In this webinar by Dr. Dean Wampler, VP of Fast Data Architecture at Lightbend, Inc., we will cut through the buzz around Fast Data and explore how to successfully exploit this new opportunity for innovation in how your organization leverages data. Specifically, Dean will review: * The business justification for transitioning from batch-oriented big data to stream-oriented fast data * The architectural and organizational changes that streaming systems require to meet their higher demands for reliability, resiliency, dynamic scalability, etc. * How some of these requirements can be met by leveraging what your organization already knows about microservice architectures
This document summarizes a webinar about inefficient Infrastructure as a Service (IaaS) pricing models and best practices for analyzing usage data. The webinar discusses how current IaaS pricing models can lead businesses to pay up to 66% more than necessary by not accounting for transient workloads. It recommends gathering usage data, looking at multiple vendor options, and benchmarking performance to establish a baseline and evaluate pricing and infrastructure changes more accurately. The webinar aims to help businesses optimize their IaaS environments for both performance and cost.
The document discusses the challenges of managing changes and versions for PeopleSoft environments. It describes how traditional version control tools only manage files and not PeopleSoft database objects. It introduces Stat ACM as a solution that can version both files and PeopleSoft objects natively. It highlights key Stat ACM capabilities like enforcing change control policies, providing audit trails of changes, facilitating rollbacks, and increasing efficiency through automation.
My talk at Confoo 2016 Montreal It is well said that "The more you sweat on the field, the less you bleed in war". Failures are an inevitable part of complex systems. Accepting that failures happen, will help you design the system's reactions to specific failures. This talks on best practices for building resilient, stable and predictable services: preventing Cascading failures, Timeouts pattern, Retry pattern,Circuit breakers and many more techniques in microservices
This document discusses common mistakes made with SQL Server and how to avoid them. It covers topics like backups, consistency checks, log cleanup, statistics maintenance, index maintenance, memory settings, parallelism settings, TempDB configuration, alerts, and power settings. The author is Tim Radney, a SQL Server MVP, who provides recommendations and scripts for ensuring databases are properly maintained and optimized.
The environment which houses your business critical EPM applications is complex. Maybe as complex as the cockpit of an aircraft. Just as a pilot might not be able to build or fix everything on their plane, you might be using applications but not know how to build or fix everything that’s being used. This shouldn’t stop you from doing a pre-flight check to ensure that all your Hyperion systems are running properly and set for you and your end users. Let’s talk about some different strategies to achieve this and give you the confidence in your systems so that you can know when things are running well—or more importantly, when they need attention before takeoff.
- SDN is a concept that separates the network control plane from the forwarding plane, allowing for centralized control over the network. It comes in three flavors: Open SDN, SDN with overlays, and SDN via APIs. - SDN is needed because traditional networking has issues like high costs, difficulty managing networks, and inability to adapt to changing traffic patterns. SDN enables more programmable, automated networks that can better serve application needs. - OpenFlow is the main southbound protocol for SDN, allowing controllers to program the forwarding behavior of network elements. It enables centralized traffic engineering and management of network flows. - For SDN to see wider adoption, a "killer app" is
Today, if events change the decision model, we wait until the next batch model build for new insights. By extending fast “time-to-decisions” into the world of Big Data Analytics to get fast “time-to-insights”, apps will get what used to be batch insights in near real time. The technology enabling this includes smart in-memory data storage, new storage class memory, and products designed to do one or more parts of an analysis pipeline very well. In this talk we describe how Ampool is building on Apache Geode to allow Big Data analysis solutions to work together with a scalable smart storage class memory layer to allow fast and complex end-to-end pipelines to be built -- closing the loop and providing dramatically lower time to critical insights.
In this guest webinar with Chris McDermott, Lead Data Engineer at HPE, learn how HPE InfoSight–powered by Lightbend Platform–has emerged as the go-to solution for providing real-time metrics and predictive analytics across various network, server, storage, and data center technologies.
This document discusses different ways to instrument software applications for monitoring purposes. It begins with definitions of instrumentation and telemetry. It then discusses the different types of data that can be collected through instrumentation like metrics and events. It describes how to instrument various parts of applications including the frontend like browsers and mobile apps as well as the backend for languages like Java, .NET, Node.js and PHP. It provides best practices for instrumentation and logging. Finally, it discusses challenges with correlating data across distributed systems and some open source options and solutions for transaction correlation.
The document provides details about Garbage First Garbage Collector (G1GC) in Java. It discusses how G1GC works, including that it divides the heap into small fixed-size regions, uses mark-sweep collection for young generations and mostly concurrent mark-sweep collection for old generations. It also provides an example of GC log output and configuration options that can be used to capture GC logs.
Understanding the basics of JVM and memory management. Understand garbage collection and the various algorthms
The document summarizes several industry standard benchmarks for measuring database and application server performance including SPECjAppServer2004, EAStress2004, TPC-E, and TPC-H. It discusses PostgreSQL's performance on these benchmarks and key configuration parameters used. There is room for improvement in PostgreSQL's performance on TPC-E, while SPECjAppServer2004 and EAStress2004 show good performance. TPC-H performance requires further optimization of indexes and query plans.
The document summarizes performance improvements in PostgreSQL versions 9.5 and 9.6. Some key improvements discussed include optimizations to sorting, hash joins, BRIN indexes, parallel query processing, aggregate functions, checkpoints, and freezing. Performance tests on sorting, hash joins, and parallel queries show significant speedups from these changes, such as faster sorting times and better scalability with parallel queries.
Monitoring of production is critical, but what you choose to monitor has a direct impact on the culture of a software development organization. At CDK Global, we focus on the end-user experience, and prioritize monitoring of their interactions with our applications. This has a direct effect of driving the culture within CDK of delivering customer delight as we continuously evolve our platform to provide world class services. Making architectural changes of legacy applications is critical, but comes with risk that the unanticipated will happen. CDK utilizes AppDynamics to monitor key application performance metrics first, to ensure refactoring work is a benefit to our clients and sets the stage for the next evolution of our platform. Key takeaways: o Drive customer delight by focusing on the end-user experience in all steps of the development process o Company culture has far reaching impact; carefully choose where to focus monitoring attention to build the culture you desire o Software architectural evolution comes with risk; guarantee that all changes benefit the end-user by monitoring key performance metrics before you begin any major technology change For more information, go to: www.appdynamics.com
In this two-hour, instructor-led hands-on lab, attendees will learn how to use the latest .Net APM features in real-life scenarios to gain operational insights into their applications. The interactive lab will cover multiple use cases, including: o Monitoring Azure web apps o Best practices monitoring ASP.NET MVC and WebAPI applications o Reasons, tips, and tricks on using service endpoints o Mastering "getter chain" skills to collect the right data The lab will include a presentation, hands-on exercises, and Q&A. To get the most out of the lab, attendees will be required to complete pre-requisite exercises and bring their own laptops. For more information, go to: www.appdynamics.com