Skip to main content

Artificial intelligence for IT operations (AIOps)


Artificial intelligence for IT operations (AIOps) is the use of deep learning and big data analytics to automate routine administrative tasks, including deployment, root cause analysis and problem resolution, for an information technology (IT) system.

Ideally, an AIOps platform brings three important capabilities to the enterprise:


  • The ability to recognize abnormal system behavior faster and with greater accuracy than humanly possible.
  • The ability to use IFTTT business rules to automate routine tasks.
  • The ability to streamline communication among stakeholders.


How AIOps works

AIOps tools gather information from the IT tools and devices already in place and apply detailed analytics and machine learning to that information in order to identify potential issues and correct them. Typically, AIOps data comes from network log files, cloud monitoring tools and helpdesk ticketing systems.

Big data technologies aggregate and organize all of the systems' output into a form that an AIOps platform can use. The platform uses correlation engines and business rules to monitor throughput and either do nothing, take action autonomously or alert a human administrator when required.

AIOps platforms are designed to illustrate dependencies and the role each dependency plays in both normal and abnormal system behavior. To be effective, AIOps tools must be adaptive to machine-learning-specific workflows and be able to handle the recursion required to support continuous machine learning (ML) model training.

Use case for AIOps

Although the underlying technologies for AIOps are relatively mature, it is still an early field in terms of combining the technologies for practical use. Organizations that want to streamline data-intensive, manual and repetitive tasks, such as ticketing, are good candidates for an AIOps platform proof-of-concept project.

Challenges of AIOps

AIOps is only as good as the data it receives and the algorithms that it is taught. The amount of time and effort needed to implement, maintain and manage an AIOps platform can be substantial. The diversity of available data sources as well as proper data storage, protection and retention are all important factors in AIOps results.

AIOps demands trust in tooling, which can be a gating factor for some businesses. For an AIOps tool to act autonomously, it must follow changes within its target environment accurately, gather and secure data, form correct conclusions based on the available algorithms and machine learning, prioritize actions properly and take the appropriate automated actions to match business priorities and objectives.


Comments

Post a Comment

Popular posts from this blog

Ghosting

Ghosting is to cease communications without notification. The use of the word "ghost" as a verb originated in social media in reference to dating, but the term is now used by employers to describe employees and potential employees who suddenly disappear. Typically, ghosting is used to describe: Job candidates who suddenly stop responding to messages. New hires who fail to show up for their first day of work. Employees who do not show up for a shift. Employees who leave work in the middle of the day and never come back. Some analysts blame ghosting on millennial entitlement. The reasoning is that members of the millennial generation have been brought up to feel they are special -- so special, in fact, that they do not need to follow conventional rules of behavior. Other analysts, however, maintain that ghosting behavior stems from changes in the job market and the phenomenon is simply a reflection of the laws of supply and demand in a healthy jo...
Post a Comment
Read more

Data deduplication

Data deduplication -- often called intelligent compression or single-instance storage -- is a process that eliminates redundant copies of data and reduces storage overhead. Data deduplication techniques ensure that only one unique instance of data is retained on storage media, such as disk, flash or tape. Redundant data blocks are replaced with a pointer to the unique data copy. In that way, data deduplication closely aligns with incremental backup, which copies only the data that has changed since the previous backup. For example, a typical email system might contain 100 instances of the same 1 megabyte (MB) file attachment. If the email platform is backed up or archived, all 100 instances are saved, requiring 100 MB of storage space. With data deduplication, only one instance of the attachment is stored; each subsequent instance is referenced back to the one saved copy. In this example, a 100 MB storage demand drops to 1 MB. Target vs. source deduplication Data deduplica...
Post a Comment
Read more

A Graphics Processing Unit (GPU)

A graphics processing unit (GPU) is a computer chip that performs rapid mathematical calculations, primarily for the purpose of rendering images. A GPU may be found integrated with a central processing unit (CPU) on the same circuit, on a graphics card or in the motherboard of a personal computer or server. In the early days of computing, the CPU performed these calculations. As more graphics-intensive applications such as AutoCAD were developed; however, their demands put strain on the CPU and degraded performance. GPUs came about as a way to offload those tasks from CPUs, freeing up their processing power. NVIDIA, AMD, Intel and ARM are some of the major players in the GPU market. GPU vs. CPU A graphics processing unit is able to render images more quickly than a central processing unit because of its parallel processing architecture, which allows it to perform multiple calculations at the same time. A single CPU does not have this capability, although multi...
Post a Comment
Read more