Observability Solution Suites Statistics


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Observability Solution Suites Statistics 2023: Facts about Observability Solution Suites outlines the context of what’s happening in the tech world.

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Top Observability Solution Suites Statistics 2023

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Observability Solution Suites “Latest” Statistics

  • High availability, reliable system-wide observation with a 99.99% uptime that doesn’t fall asleep at the wheel incident inquiry is simple to make sure you have all the information you need, gather and save all pertinent metrics.[1]
  • Reduce redundant notifications by up to 90% by automatically correlating events and alerts from any source.[2]
  • By automatically connecting alerts and events from any source, you may cut down on duplicate warnings by up to 90%.[3]
  • Compared to 15% of newcomers, 45% of observability leaders report introducing eight or more new products/revenue streams in the last year.[4]
  • 57% of respondents cited lack of context as the biggest issue with their current monitoring tools.[4]
  • The complexity of managing hybrid multi-cloud setups, according to 58% of executives, is their biggest difficulty.[4]
  • Only 31% of novices and 70% of observability leaders think they have outstanding visibility in their organization’s security position.[4]
  • 74% of CIOs think the managing performance might become challenging as complexity increases.[4]
  • In cloud-native architectures, 76% of CIOs claim that they lack total insight into application performance.[4]
  • Observability solutions provide information on service outages to 78% of software leaders compared to just 12% of laggards.[4]
  • 20% of C-suite executives expect budget increases that are large next year, according to 81% of C-suite executives. ?yed engineers employ hundreds or even thousands of compute instances, along with a lot of containers and microservices.[4]
  • 86% of respondents mention technological challenges, including poor legacy tools and a lack of platform alternatives.[4]
  • The architecture or observability solutions must function, according to 87% of respondents.[4]
  • 91% of data center facilities managers who were questioned reported having dealt with at least one disruptive occurrence in the previous 12 months, including downtime caused by an outage.[4]
  • 82% of businesses have a hybrid cloud approach, while 92% of businesses have a multi-cloud strategy.[4]
  • According to 94% of software executives, observability is essential for creating software.[4]
  • Due to fragmented technologies and laborious human work, business firms cannot monitor 95% of their applications.[4]
  • 99% of executives claim that their culture and observability technologies enable developers to act quickly without worrying about the consequences.[4]
  • 70% of CIOs claim that real-time monitoring of containerized microservices is almost hard.[4]
  • For 90% of surveyed developers, monitoring massively distributed applications presents issues that are orders of magnitude more than those that conventional monitoring solutions can handle.[4]
  • 57% of respondents said their present monitoring tools’ lack of context was their biggest problem.[4]
  • 86% of respondents to Splunk’s survey mention technological challenges, such as poor legacy tools, a lack of platform alternatives, worries about open source tools, and tool fragmentation, as a barrier to the adoption of observability.[4]
  • 87% of survey participants said it’s critical that observability solutions function independently of the architecture.[4]
  • 92% of engineers questioned think observability tools promote better decisions.[4]
  • The size of the worldwide cloud computing market is anticipated to reach 1,251.09 billion by 2028, growing at a CAGR of 19.1% from 2021 to 2028.[4]
  • 82% of businesses using cloud infrastructure workloads say they’ve spent money that wasn’t required.[5]
  • Because of severe data system performance concerns, 50% of imported data was often not processed for true digital.[5]
  • Because of this, the business could maintain 99.97% availability even while its data infrastructure grew by 2,000%.[5]
  • Cost overruns for public cloud services will affect 60% of infrastructure and operations directors.[5]
  • Acceldata could assist PubMatic in optimizing its HDFS cluster and decreasing its block footprint by 30% in such a large.[5]
  • Authors Sarah Wang and Martin Casado contend that businesses may be able to save anywhere between 30% and 50% of their overall cloud expenditures in that op.[5]
  • Business leaders are dissatisfied with data quality in 73% of cases, and just 61% of firms can use data to preserve a competitive advantage.[6]
  • On average, in 2022, data professionals will devote 40% of their day to problems with data quality.[7]
  • Kingold fixes 95% of its key problems before they influence consumers and can identify performance issues 10x quicker.[8]
  • Businesses may save up to 60% on operational management expenditures by using oracle enterprise manager.[8]

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How Useful is Observability Solution Suites

Observability solution suites typically consist of a range of monitoring tools, including logs, metrics, and traces, that work together to provide a comprehensive view of a system. By analyzing data from various sources, these tools can help organizations pinpoint the root cause of issues, optimize their systems for peak performance, and proactively address potential problems before they escalate.

One of the key benefits of observability solution suites is their ability to provide real-time visibility into the health and performance of a system. By continuously monitoring various aspects of a system, businesses can identify and address issues as they occur, rather than waiting for them to impact operations or, worse, customers. This proactive approach can help organizations minimize downtime, improve overall system reliability, and ultimately enhance the customer experience.

Another advantage of observability solution suites is their ability to centralize monitoring and troubleshooting efforts. Instead of having to rely on disparate tools and systems to monitor different aspects of their operations, businesses can use a single platform to gain a holistic view of their systems. This centralized approach not only makes it easier to monitor and analyze data but can also streamline the troubleshooting process, enabling teams to collaborate more effectively and resolve issues more efficiently.

Moreover, observability solution suites can help businesses better understand the relationships between different components of their systems. By correlating data from logs, metrics, and traces, organizations can gain insights into how various parts of their systems interact and impact one another. This can be particularly valuable in a complex, distributed system where issues in one area can have far-reaching effects across the entire system.

In addition to these benefits, observability solution suites can also enable organizations to make more informed decisions about their systems. By providing detailed insights into system performance and behavior, businesses can identify areas for improvement, optimize their resources, and make strategic decisions to better align with their business goals. This data-driven approach can help organizations drive innovation, increase efficiency, and ultimately achieve a competitive edge in the market.

Overall, observability solution suites have proven to be invaluable tools for businesses looking to monitor and optimize their systems. By providing real-time visibility, centralizing monitoring efforts, understanding system relationships, and enabling data-driven decision-making, these tools can help organizations improve their operations, enhance their customer experience, and stay ahead of the competition in today’s rapidly evolving digital landscape.

Reference

  1. aiven – https://aiven.io/solutions/aiven-for-observability
  2. atlan – https://atlan.com/data-observability-tools/
  3. newrelic – https://newrelic.com/platform
  4. signoz – https://signoz.io/learn/why-is-observability-critical-for-cloud-native-applications/
  5. acceldata – https://www.acceldata.io/blog/data-observability-80x-roi
  6. ibm – https://www.ibm.com/blogs/journey-to-ai/2022/07/dont-let-your-data-pipeline-slow-to-a-trickle-of-low-quality-data/
  7. montecarlodata – https://www.montecarlodata.com/blog-data-observability-first-data-catalog-second-heres-why/
  8. oracle – https://www.oracle.com/manageability/

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