When Amazon launched Alexa or when Google acquired Deepmind the use cases that are emerging today would have been unthought of by many. Today AI and bots are redefining how users engage with devices. The near real-time translation of languages, the capability of Alexa to decipher the millions of accents all have an Machine Learning underpinning. What we now take for granted in technology was once a dream, an impossibility in the minds of many. With new advancements emerging each day, technology has come a long way. Artificial Intelligence (AI) is touted as the next big thing, an inevitable game changer. There is more investment going into AI and voice assistance today than ever. The technology rests on deep learning and pattern recognition.
Big data was once limited to processing batches of huge, unstructured data collected by organizations over time. Apart from the heavy investment, it had the additional disadvantage of producing delayed results. Real-time operations, on the other hand, hold the advantage of making businesses extremely responsive to customer data. Over time, organizations have realised that remaining relevant and updated calls for a real-time monitoring of data.
The idea of DevOps is still nascent in the technology domain. Although a number of software development teams still might not completely be aware of it, DevOps assumes a crucial role to the teams. As It involves automation and systems administration. DevOps engineers have a combination of specialized aptitudes and skills, depending on a mix of business, organizational and domain capabilities to best help the group or client he or she is supporting to move towards a seamless deployment model. There is no fail-proof process to identify a DevOps engineer, but we will try and create an outline of the things that need to be kept in mind.
These days, DevOps and Agile are two of the most frequently used terms in the software development lifecycle context, though the debate of benefits of DevOps also continues. When Agile philosophy had started gaining traction in late 90’s It was focussed on the key matrix of accelerating software development. With the emergence of DevOps, this journey is reaching another scale, where its not only the development team which is undergoing transformation but also the infrastructure teams that are changing in how they deploy the solution.
Most Organisations looking to increase the efficiency of their software development and aiming to move towards a faster and a more effective way of deploying solutions have taken to Microservices. The n-tier database driven application that is represented by monolithic architectures has its own challenges including scalability and responsiveness.
Serverless computing and Container driven development is becoming mainstream and the idea that operating systems can be virtualized to run individual pieces of applications is transforming how computing is evolving. It is important for any organization to understand the process of adopting containers in their firm and how it will affect the technological and cultural transformation.
When conversations around Agile started around two decades back, few would have thought that this radically new approach towards software development would take such a long period of time to become mainstream. With Agile now the centerpiece of software development methodology the focus on rapid prototyping, frequent releasesand close collaboration with various stakeholders is clearly visible.
AWS deployment best practices With more than 47% market share in the public cloud market, Amazon Web Services (AWS) is a de facto leader in this domain. It has been able to achieve this by undertaking various activities including building a high level of trust based relationship with technology leaders and developing solutions that are loved by the developer community.
With the maturing of the cloud technology stack along with addressing of concerns around security, there has been a significant adoption of cloud within enterprises. Cloud service providers like Microsoft Azure and AWS have added functionalities like data warehousing and serverless computing to meet the evolving requirement of dynamic enterprises.
With cloud adoption increasing exponentially, the role of IT is evolving from simply undertaking infrastructure planning to designing and deploying platforms that provide optimal performance. Enterprises today have multiple choices between cloud infrastructure at varying price points and performance levels. Find out which is better suited for your application.