In a final report, Splunk highlights the benefits of implementing the observation and highlights a specific delay in France. Application downtime costs vary from more than a single to triple depending on the maturity of adoption.
From reporting server logs to monitoring web performance and containerized applications, including security indicators, monitoring activities have become more complex over time. With the birth of the concept of observability to consider this evolution and where a large number of players (AppDynamics, BMC Software, New Relic, Sysdig, etc.) or historical specialists in such data analysis machines of Splunk. To determine the maturity of companies in this area, the publisher published the second edition of its report The State of Observability. “Still a relatively new discipline, observationalism has continued to evolve in the years since our first State of Observability report,” Splunk said. “The haste of cloud adoption during a pandemic has exacerbated monitoring challenges for traditional IT teams.”
In its study in which 1,250 IT managers and operational staff participated, Splunk said convergence is expected between different tools, services and teams resulting from application performance monitoring (APM), networks ( NPM), security and of course the management and analysis of records. And this in a context already marked by the evolution of IT systems, organizations and developments where 96% of organizations are already working on some native cloud application in some environment. It is known that two-thirds of the companies surveyed expect an increase in the proportion of cloud-native apps by 2023. “The study also shows that the value of observability is proven and understood. The question is how companies continue to improve their visibility and responsiveness to increasingly dynamic infrastructure, ”Splunk said.
Improve visibility and application development times
The results of The State of Observability 2022 report show a segmentation of respondents (leader, intermediate and novice) according to the maturity of their company in terms of observability. For this, 4 factors are considered (experience, data correlation, rationalization of solutions and adoption of AI/ML technologies). “Every year, confidence increases signaling increasing observation success at all levels. But twice as many leaders than novices (71% vs. 35%) are highly confident that they can meet application availability and performance requirements, ”Splunk said in its report. “66% of leaders say their visibility in application performance is good compared to only 44% for beginners. Similarly, 64% of leaders say their visibility in their security posture is good (compared to 42 % of beginners), 58% had good visibility in application-level code (compared to 43%), and 64% had good visibility in containers (compared to up to 39%).
The benefits of observation -related use can be found in terms of the time required to identify and solve application performance problems. Respondents in the lead category were more likely than beginners to know that observation solutions helped speed up development times (68% vs. 57%). In terms of turnaround and deployment speed (73% vs. 62%), better visibility in cloud native and traditional applications (75% vs. 58%). But so is the accelerated detection of problems (75% versus 65%, as well as their solving (73% versus 65%) .In terms of tools focused on observation, most respondents (between of 33% and 36% depending on their level of maturity) agree to offer between 11 and 15 solutions to meet this challenge. ”79% of respondents say their organization has added of tools and capabilities in their observability portfolio; only 8% combined. At the same time, 48% of organizations partner with fewer vendors compared to 35% who say they are increasing them, “Splunk found .
Service delay costs that may increase
Splunk also looked at application downtime costs, which vary by observability maturity level, from $ 2.5 million for leaders to $ 7.9 million for middlemen and 23, $ 8 million for less advanced. Among the major fears related to decreased uptime, we saw – on average – a decrease in customer satisfaction (53%), loss of revenue (48%), reputation (44%) or even customers (39 %). The editor also asked why organizations started implementing tracking. The most frequent answer is not surprising, especially as it generally improves app performance and/or user experience. The second answer is even more surprising because it is linked to the ability to attract talent: “although it came second overall, it was the best answer given by leaders who chose it at 68% compared to 56% for beginners.”
The study also provides some interesting indicators by country, including France. In key lessons, it appears that French organizations lag behind in their observation journey: 74% are novices (compared to 58% on average in other countries) and only 5% are leaders (compared to 10% in other part 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 the average of 43% in other countries. .
More compartmentalized observability tools in France
French companies are not very optimistic about the future of cloud-native applications: 46% say a larger proportion of their developed applications will be cloud-native compared to the average of 69% in other countries. French organizations also tend to have more compartmentalized observability tools with only 20% of respondents in France reporting significant data correlation between solutions compared to 38% on average in other countries. . Furthermore, only 19% of French organizations stated that they use AI/ML intensively in their range of observability tools, compared to 28% elsewhere.