Survey: Companies Can’t Get All the Benefits of the SaaS Triangle
Opsani, the leading provider of AI-driven optimization for cloud applications, released the results of a month-long poll* completed by more than 600 DevOps engineers at SaaS companies, which demonstrates the struggle companies have when trying to optimize cloud applications’ regular code changes and application performance, against operating budgets.
An optimized SaaS triangle, which describes how an application services provider benefits from an optimized mix of code delivery, application performance and budget for hosting those applications, has become increasingly complex as enterprises transition away from on-prem infrastructure and to cloud-native ones. About 93 percent of forward-looking companies have currently adopted a multi-cloud strategy, with the remaining ones following suit. IDC reports a massive $233.4 billion in overall global cloud revenue, which is 26 percent higher than last year.
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On top of this, COVID-19 has been a forcing function for digital transformation. According to a report from Yellowbrick, 43.5 percent of companies have accelerated their move to the cloud as a result of the crisis. 59 percent of enterprises anticipate their cloud spend to exceed their budget plans, and 82 percent of companies are willing to pay more to ensure increased flexibility in their cloud systems.
The rush to cloud comes with costly complexities. Our recent blind poll indicated that 91 percent of SaaS business leaders feel their cloud applications perform efficiently—meaning top executives feel they are getting the most value from their cloud investments at the lowest cost. Today’s survey results of DevOps engineers say otherwise:
- When asked ‘Does your organization release software updates in weekly, daily or hourly sprints?’
- 59 percent said weekly;
- 28 percent said daily
- four percent even said ‘hourly.’
- When asked ‘When pushing out new code updates, is it more important that the application’
- Is launched as fast as possible – 31 percent
- Is ‘good enough-not too buggy’ – 30 percent
- Doesn’t go down or fail – 18 percent
- Has enough resources – eight percent
- Is tuned for efficiency – 14 percent
- How often does your organization optimize its application stack?
- Regularly – 76 percent
- Only in emergencies – 17 percent
- My organization does not optimize its application stack – four percent
- Does your organization deploy its mainstream applications on containers, or plan to do so?
- Yes – 48 percent
- Yes, has plans to – 40 percent
- No, and has no plans to – 7 percent
- What issues do managers in your department emphasize the most?
- Staying in a certain budget – 33 percent
- Maximizing resources (CPU, bandwidth, etc.) – 43 percent
- Making sure cloud apps maintain uptime – 20 percent
- What are your service level objectives or performance goals for any of your applications or services you offer?
- Transactions per second – 50 percent
- IOps – 28 percent
- Latency – 41 percent
- Throughput – 40 percent
- Dollar per transaction – 37 percent
Overwhelmingly, IT departments and management feel their applications are optimized for the code to run as efficiently in production environments at the lowest cost. But the survey results say something else. A simple four container application has trillions of possible efficiency parameters that need to be continuously tuned to reach optimum performance for the lowest cost—meaning, achieving the SaaS Triangle is too complex for people to do without automation.
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Here’s why: 61 percent of survey responses said that new code was being released as fast as possible, or ‘not too buggy.’ Almost 20 percent of respondents said they optimize their stacks ‘only in emergencies.’ Managers are split on what they emphasize the most from their application teams: 33 percent said budget; 43 percent say maximizing resources; and 20 percent said maintaining application uptime was the most important factor for them. In this fractured scenario, no company can achieve the benefits of the SaaS triangle without the help of automated tools.
Luckily, when asked ‘Does your organization augment your work with AI tools for faster decision-making purposes?’ 57 percent answered yes, 34 percent said no, but planned to; and only 7 percent said no and had no plans to, meaning there is a realization among service providers that they actually could be doing a lot more to maximize the performance of their applications, control their budget and focus on bringing better code and services to their users.
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