In a final report, Splunk highlights the benefits of implementing observability and highlights a certain delay in France. Application downtime costs vary from more than a single to a triple depending on adoption maturity.
From reporting server logs to monitoring the performance of web and containerized applications, including security indicators, monitoring activities have become more complex over time. With the birth of the concept of observability to take this evolution into account and which a large number of players (AppDynamics, BMC Software, New Relic, Sysdig, etc.) or historical specialists in machine data analysis like Splunk. To identify the maturity of companies in this area, the publisher has published the second edition of its report The State of Observability. “Still a relatively new discipline, observability has steadily gained ground in the year since our first State of Observability report,” says Splunk. “The rush of cloud adoption during the pandemic has exacerbated the monitoring challenges for traditional IT teams.”
In its study in which 1,250 IT managers and operational staff participated, Splunk notes that convergence is expected between the various tools, services and teams resulting from the monitoring of application performance (APM), networks (NPM), security and of course the management and analysis of logs. And this in a context already marked by the evolution of systems, organization and IT developments where 96% of organizations are already working with certain native cloud applications on several environments. Knowing that two-thirds of companies surveyed expect an increase in the proportion of cloud-native apps in 2023. “The study also shows that the value of observability has been proven and understood. The question is how companies continue to improve their visibility and responsiveness across increasingly dynamic infrastructures,” says Splunk.
Improve visibility and application development times
The results of The State of Observability 2022 report reflect a segmentation of respondents (leader, intermediate and beginner) according to the maturity of their company in terms of observability. For this, 4 factors were taken into account (experience, data correlation, rationalization of solutions and adoption of AI/ML technologies). “Year after year, confidence has increased signaling increased observability success at all levels. Yet twice as many leaders as newbies (71% vs. 35%) are completely confident that they can meet application availability and performance requirements,” Splunk notes in its report. “66% of leaders say their visibility into application performance is excellent compared to only 44% for beginners. Similarly, 64% of leaders say visibility into their security posture is excellent (vs. 42% of beginners), 58% have excellent visibility into application-level code (vs. 43%), and 64% have excellent visibility into containers (compared to 39%)”.
The usage benefits related to observability are found in terms of the time required to detect and resolve application performance problems. Respondents in the leader category were more likely than beginners to find that observability solutions helped speed up development times (68% versus 57%). Ditto in terms of speed of turnaround and deployment (73% vs. 62%), better visibility into cloud native and traditional applications (75% vs. 58%). But also the accelerated detection of problems (75% against 65%, as well as their resolution (73% against 65%). In terms of tools devoted to observability, a majority of respondents (between 33% and 36% depending on their level of maturity) agrees to dedicate between 11 and 15 solutions to meet this challenge. “79% of respondents say that their organization has added tools and capabilities to their observability portfolio; only 8% are consolidating. In the same time, 48% of organizations are partnering with fewer vendors versus 35% who say they are increasing them,” Splunk finds.
Service interruption costs that can skyrocket
Splunk also looked at application downtime costs, which vary by observability maturity level, ranging from $2.5 million for leaders to $7.9 million for middlemen and 23, $8 million for the less advanced. Among the main fears related to the decrease in availability times, we find – on average – the drop in customer satisfaction (53%), the loss of income (48%), reputation (44%) or even customers ( 39%). The editor also asked why organizations had started implementing monitoring. The most frequent answer was the least surprising, namely to generally improve app performance and/or user experience. The second answer was more surprising since it was linked to the ability to attract talent: “although it came second overall, it was the best answer given by the leaders who chose it at 68% compared to 56% for beginners.”
The study also provides some interesting indicators by country, including France. Among the main lessons, it appears that French organizations are lagging behind in their observability journey: 74% are beginners (compared to 58% on average in other countries) and just 5% are leaders (compared to 10% in the rest of the world). French companies more often report that their investments in AIOps technologies have helped them achieve a lower mean time to repair (MTTR) at 58% compared to an average of 43% in other countries.
More compartmentalized observability tools in France
French companies are also less optimistic about the future of cloud-native applications: 46% say that a greater proportion of their developed applications will be cloud-native compared to an average of 69% in other countries. French organizations also tend to have more compartmentalized observability tools with only 20% of respondents in France reporting a significant correlation of data between solutions versus 38% on average in other countries. Furthermore, only 19% of French organizations declare that they use AI/ML intensively in their set of observability tools, compared to 28% elsewhere.
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