Six DevOps Misconceptions Debunked: The road to DevOps success is littered with myths and misconceptions
Here are the largest potholes you need to avoid;
While DevOps is firmly grounded in reality, numerous myths and misconceptions have grown up around the concept, several of which have prevented organizations from getting the most out of their teams.
Is your organization functioning under one or more DevOps misconceptions? Here’s a rundown of the six top myths you need to avoid.
1. DevOps is a cultural transformation that can’t happen quickly or be mandated
Culture does not transform; humans transform when inspired to do so, observed Jayne Groll, CEO of DevOps Institute, a professional organization. “While we know that cultural transformation is as critical to DevOps as digital transformation, culture is often painted as a single ‘thing’ that can be transformed or changed,” she said.
Culture is, in fact, a complex mesh of social and psychological interactions and behaviors that affect how humans perceive their work environment, management support, and peer-to-peer relationships. “Changing the way humans think, behave and work is not easy and requires a different set of strategic and tactical initiatives that do not involve automation or technology,” Groll noted.
The most successful DevOps organizations are those that visibly invest in people. Such organizations have shifted their organizational design, hired coaches, launched hackathon days, and provided ongoing opportunities for their teams to get upskilled. “This approach not only expedites flow, but it also makes these organizations highly attractive to top talent,” Groll said.
2. DevOps is all about tools and automation
Although automation is essential at different stages across DevOps, it’s also important to establish the right practices and culture before addressing automation, stated Prasanna Singaraju, CTO and co-founder of Qentelli, an IT services company focusing on several areas, including DevOps. “If current processes that do not lend themselves to DevOps are automated, it will only lead to accelerated chaos,” he noted. “Also, investing in tools and resources and hoping they will somehow magically solve problems will only lead to lost time and demotivated teams.”
This article originally appeared on informationweek.com To read the full article, click here.
Nastel Technologies uses machine learning to detect anomalies, behavior and sentiment, accelerate decisions, satisfy customers, innovate continuously. To answer business-centric questions and provide actionable guidance for decision-makers, Nastel’s AutoPilot® for Analytics fuses:
- Advanced predictive anomaly detection, Bayesian Classification and other machine learning algorithms
- Raw information handling and analytics speed
- End-to-end business transaction tracking that spans technologies, tiers, and organizations
- Intuitive, easy-to-use data visualizations and dashboards
If you would like to learn more, click here.
Nastel Technologies is the global leader in Integration Infrastructure Management (i2M). It helps companies achieve flawless delivery of digital services powered by integration infrastructure by delivering Middleware Management, Monitoring, Tracking, and Analytics to detect anomalies, accelerate decisions, and enable customers to constantly innovate, to answer business-centric questions, and provide actionable guidance for decision-makers. It is particularly focused on IBM MQ, Apache Kafka, Solace, TIBCO EMS, ACE/IIB and also supports RabbitMQ, ActiveMQ, Blockchain, IOT, DataPower, MFT and many more.
The Nastel i2M Platform provides:
- Secure self-service configuration management with auditing for governance & compliance
- Message management for Application Development, Test, & Support
- Real-time performance monitoring, alerting, and remediation
- Business transaction tracking and IT message tracing
- AIOps and APM
- Automation for CI/CD DevOps
- Analytics for root cause analysis & Management Information (MI)
- Integration with ITSM/SIEM solutions including ServiceNow, Splunk, & AppDynamics