Civil Rights
Movements, leaders, victories and the continuing fight for equality.
q2K BHP
Black History Portal
THE BHP WIRE —
HIDDEN TRUTHS
What's New!
Explore the people, places, events, achievements, struggles and stories that shaped our journey.
Movements, leaders, victories and the continuing fight for equality.
Innovation, patents, science, technology and world-changing contributions.
Pioneers, champions, Negro Leagues, records, activism and excellence.
Meet the people whose lives, choices and achievements shaped the journey.
Black towns, communities, institutions and places where history happened.
Moments that changed communities, movements, institutions and the nation.
Wilmington, North Carolina once had a thriving Black middle class and an elected interracial government. In 1898 white supremacists used violence to overthrow that government, kill Black residents and drive many others from the city.
MORE →Reflects the personal views, recollections, and perspective of the author, Mike Davis.
This is a personal recollection on the Move fire on May 13, 1985
In the fields of information technology and systems management, application performance management (APM) is the monitoring and management of the performance and availability of software applications. APM strives to detect and diagnose complex application performance problems to maintain an expected level of service. APM is "the translation of IT metrics into business meaning ([i.e.] value)."[1]
The term monitoring was replaced by many tool vendors by the term Observability. Often, monitoring is seen as the technical process of data collection, whereas observability is seen as the capability to understand a systems behavior.[2]
Two sets of performance metrics are closely monitored. The first set of performance metrics defines the performance experienced by end-users of the application. One example of performance is average response times under peak load. The components of the set include load and response times:
The second set of performance metrics measures the computational resources used by the application for the load, indicating whether there is adequate capacity to support the load, as well as possible locations of a performance bottleneck. Measurement of these quantities establishes an empirical performance baseline for the application. The baseline can then be used to detect changes in performance. Changes in performance can be correlated with external events and subsequently used to predict future changes in application performance.[4]
The use of APM is common for Web applications, which lends itself best to the more detailed monitoring techniques.[5] In addition to measuring response time for a user, response times for components of a Web application can also be monitored to help pinpoint causes of delay. There also exist HTTP appliances that can decode transaction-specific response times at the Web server layer of the application.
In their APM Conceptual Framework, Gartner Research describes five dimensions of APM:[6][7][8][9]
In 2016, Gartner Research updated its definition, into three main functional dimensions:[10]
Measuring application performance causes overhead, that might also influence the user experience. The overhead can be reduced by several technical measures, including reducing the amount of monitored events [11] and aggregation of data before serialization.[12]
Since the first half of 2013, APM has entered into a period of intense competition in technology and strategy with a multiplicity of vendors and viewpoints.[13] This has caused an upheaval in the marketplace with vendors from unrelated backgrounds (including network monitoring, systems management, application instrumentation, and web performance monitoring) adopting messaging around APM[which?]. As a result, the term APM has become diluted and has evolved into a concept for managing application performance across many diverse computing platforms, rather than a single market.[clarification needed][14] With so many vendors to choose from, selecting one can be a challenge. It is important to evaluate each carefully to ensure its capabilities meet your needs.[15]
Two challenges for implementing APM are (1) it can be difficult to instrument an application to monitor application performance, especially among components of an application, and (2) applications can be virtualized, which increases the variability of the measurements.[16][17] To alleviate the first problem application service management (ASM) provides an application-centric approach, where business service performance visibility is a key objective. The second aspect present in distributed, virtual and cloud-based applications poses a unique challenge for application performance monitoring because most of the key system components are no longer hosted on a single machine. Each function is now likely to have been designed as an Internet service that runs on multiple virtualized systems. The applications themselves are very likely to be moving from one system to another to meet service-level objectives and deal with momentary outages.[18]
Applications themselves are becoming increasingly difficult to manage as they move toward highly distributed, multi-tier, multi-element constructs that in many cases rely on application development frameworks such as.NET or Java.[19] The APM Conceptual Framework was designed to help prioritize an approach on what to focus on first for quick implementation and overall understanding of the five-dimensional APM model. The framework slide outlines three areas of focus for each dimension and describes their potential benefits. These areas are referenced as "Primary" below, with the lower priority dimensions referenced as "Secondary. "[20]
Measuring the transit of traffic from user request to data and back again is part of capturing the end-user experience (EUE).[21] The outcome of this measuring is referred to as Real-time Application monitoring (aka Top-Down monitoring), which has two components, passive and active. Passive monitoring is usually an agentless appliance implemented using network port mirroring. A key feature to consider is the ability to support multi-component analytics (e.g., database, client/browser)[22]. Active monitoring, on the other hand, consists of synthetic probes and web robots predefined to report system availability and business transactions. Active monitoring is a good complement to passive monitoring; together, these two components help provide visibility into application health during off-peak hours when transaction volume is low[23].
User experience management (UEM) is a subcategory that emerged from the EUE dimension to monitor the behavioral context of the user. UEM, as practiced today, goes beyond availability to capture latencies and inconsistencies as human beings interact with applications and other services.[24] UEM is usually agent-based and may include JavaScript injection to monitor the end-user device. UEM is considered another facet of Real-time Application monitoring.
When preparing to implement a runtime application architecture, it is necessary to ensure that up/down monitoring is in place for all nodes and servers within the environment (aka, bottom-up monitoring). This helps lay the foundation for event correlation and provides the basis for a general understanding of how network topologies interact with application architectures.
 |
Focus on user-defined transactions or the URL page definitions that have some meaning to the business community. For example, if there are 200 to 300 unique page definitions for a given application, group them into 8–12 high-level categories. This allows for meaningful SLA reports, and provides trending information on application performance from a business perspective: start with broad categories and refine them over time. For a deeper understanding, see Business transaction management.
|
Deep dive component monitoring (DDCM) requires an agent installation and is generally targeted at middleware, focusing on web, application, and messaging servers. It should provide a real-time view of the J2EE and .NET stacks, tying them back to the user-defined business transactions. A robust monitor shows a clear path from code execution (e.g., spring and struts) to the URL rendered, and finally to the user request. Since DDCM is closely related to the second dimension in the APM model, most products in this field also provide application discovery dependency mapping (ADDM) as part of their offering.
Source: Wikipedia. Article content is retrieved live through the MediaWiki API.
In the fields of information technology and systems management, application performance management (APM) is the monitoring and management of the performance and availability of software applications. APM strives to detect and diagnose complex application performance problems to maintain an expected level of service. APM is "the translation of IT metrics into business meaning ([i.e.] value)." The term monitoring was replaced by many tool vendors by the term Observability. Often, monitoring is seen as the technical process of data collection, whereas observability is seen as the capability to understand a systems behavior.
Application service management (ASM) is an emerging discipline within systems management that focuses on monitoring and managing the performance and quality of service of business transactions. ASM can be defined as a well-defined process and use of related tools to detect, diagnose, remedy, and report the service quality of complex business transactions to ensure that they meet or exceed end-users Performance measurements relate to how fast transactions are completed or information is delivered to the end-user by the aggregate of applications, operating systems, hypervisors (if applicable), hardware platforms, and network interconnects. The critical components of ASM include application discovery & mapping, application "health" measurement & management, transaction-level visibility, and incident-related triage. Thus, the ASM tools and processes are commonly used by such roles as Sysop, DevOps, and AIOps. ASM is related to application performance management (APM) but serves as a more pragmatic, "top-down" approach that focuses on the delivery of business services. In a strict definition, ASM differs from APM in two critical ways. APM focuses exclusively on the performance of an instance of an application, ignoring the complex set of interdependencies that may exist behind that application in the data center. ASM specifically mandates that each application or infrastructure software, operating system, hardware platform, and transactional "hop" be discretely measurable, even if that measurement is inferential. This is critical to ASM's requirement to be able to isolate the source of service-impacting conditions. APM often requires instrumentation of the application for management and measurability. ASM advocates an application-centric approach, asserting that the application and operating system have comprehensive visibility of an application's transactions, dependencies, whether on-machine or off-machine, as well as the operating system itself and the hardware platform it is running on. Further, an in-context agent can also infer network latencies with a high degree of accuracy, and with a lesser degree of accuracy when the transaction occurs between instrumented and non-instrumented platforms. Application service management extends the concepts of end-user experience management and real user monitoring in that measuring the experience of real users is a critical data point. However, ASM also requires the ability to quickly isolate the root cause of those slow-downs, thereby expanding the scope of real user monitoring/management. The use of application service management is common for complex, multi-tier transactional applications. Further, the introduction of service-oriented architecture and microservices approaches together with hypervisor-based virtualization technologies have proven a catalyst for the adoption of ASM technologies, as complex applications are disproportionately impacted by the introduction of hypervisors into an existing environment A study by the Aberdeen Group indicates that most deployments of virtualization technologies are hampered by their impact on complex transactional applications. More and more often ASM approaches are equipped in automated adaptive controllers that consider service-level agreement, cloud computing, real-time and energy-aware application controller targets.
Performance management work (PMW) describes all activities that are necessary to ensure that performance requirements of application systems (AS) can be met. Therefore, PMW integrates software performance engineering (SPE) and application performance management (APM) activities. SPE and APM are part of different lifecycle phases of an AS, namely systems development and IT operations. PMW supports a comprehensive coordination of all SPE and APM activities, which is inevitable due to an increased complexity of AS architectures. The term "performance management work" was first introduced by Brunnert et al. (2014) in Business & Information Systems Engineering as well as in the German WIRTSCHAFTSINFORMATIK.
Systems management is enterprise-wide administration of distributed systems including (and commonly in practice) computer systems. Systems management is strongly influenced by network management initiatives in telecommunications. The application performance management (APM) technologies are now a subset of Systems management. Maximum productivity can be achieved more efficiently through event correlation, system automation and predictive analysis which is now all part of APM.
Before the 1921 destruction of Tulsa’s Greenwood District, Black residents had created a remarkable center of business and community life. The district included stores, professional offices, entertainment venues and homes owned by Black citizens. Understanding Greenwood means learning what was built—not only what was burned.
MORE →Madam C.J. Walker