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Highlights from AWS re:Invent 2021

Posted on October 28, 2022 by

Categories: AWS

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Tens of thousands go to Las Vegas at the end of the year to take part in AWS re:Invent. Since 2012, AWS re:Invent has served as the benchmark event for engineers who specialise in the cloud, providing a forum for the exchange of cutting-edge knowledge and solutions among members of the worldwide cloud computing community.

AWS adopted a hybrid format with both in-person and virtual activities for this year’s conference after turning totally virtual in November of previous year. In addition to presentations and workshops on health and technology, re:Invent 2021 featured a Health and Life Sciences Lounge for delegates from the industry to delve further into health-related issues. The need of minimising biases while using machine learning techniques in observability and predictive models for big companies, as well as diversity, equity, and inclusion, were also emphasised. The subjects of security, accessibility, and improvement of cloud technology were combined with these two issues.

This year, Datadog had three booths; our main exhibit provided demos, while our smaller booths concentrated on in-depth examinations of Datadog’s most recent developments and machine learning capabilities. On the main stage, we also had a few speaker series with presentations from Datadog and our partners. I spoke with Nathan Case, Senior Director of Security Operations at Resilience, on the importance of automating instrumentation and providing context for alarms as we demonstrated how firms can scale effectively using improved observability and security strategies. Kirk Kaiser from Datadog and Jeff Nickoloff, senior principal engineer at Paypal, also spoke on adding purposeful and sympathetic observability to dashboards, highlighting the significance of utilising dashboards to address the appropriate issues in relation to your business and product.

At re:Invent 2021, Datadog

At this year’s conference, there were a tonne of other incredible speakers, businesses, and innovations. In this article, we’ll look at some of the show’s high points and discuss what it was like to attend re:Invent 2021 again in person.

Cloud refinement

Building on the success of cloud technology over the previous ten years, several manufacturers this year showed improvements and upgrades to current products and platforms rather than launching new ones. Cloud computing is now the standard choice for many businesses, according to AWS CEO Adam Selipsky, who called it “an enabler of a fundamental transformation in the way that company runs” in his keynote address. At re:Invent 2021, the focus on new features and upgrades was a key sign of how successful the cloud sector has grown.

One of Selipsky’s major announcements was the addition of cell-level security to AWS Lake Formation. If you are unfamiliar with Lake Formation, picture it as a huge spreadsheet that organises all of your data lakes. With the capabilities of AWS IAM and KMS, you can now give access or limit on a cell-by-cell basis rather than everyone seeing all the individual rows and columns, making the hardest difficulty simply categorising data. Visit their page describing AWS Lake Formation for additional details.

Availability and simplicity

It’s hardly surprising that finding builders to hire is difficult for everyone. Every form of technical resource is in limited supply, and AWS and customer breakouts during re:Invent 2021 accentuated this situation. It is obvious that AWS is committed to expanding the pool of cloud builders from the AWS Community Builders programme to the broad list of certification pathways for DevOps, machine learning, and many more. We also witnessed a big product shift this year toward the development of low-code and no-code solutions to empower people who are not as oriented toward software engineering.

Using SageMaker Canvas to dismantle silos

With the introduction of Amazon SageMaker Canvas, a visual, no-code machine learning capability for business analysts, new low-code solutions emerged on the first day. By simply maintaining data on a single platform and enabling business stakeholders to observe and comprehend all the key phases of the machine learning modelling process, SageMaker Canvas is unique in that it is made to break down silos across the machine learning pipeline. There are fewer copies of the data streaming over the network as a consequence, which helps to save time and eliminate mistakes. Here are additional details about AWS SageMaker Canvas.

Lab and accessible machine learning with SageMaker Studio

In case SageMaker Canvas wasn’t enough to get businesses interested in machine learning, AWS also unveiled SageMaker Studio Lab. SageMaker Studio Lab is a free, no-setup development environment that aims to make machine learning accessible to everyone and lower the hurdles to understanding its principles. It’s thrilling to think about the potential uses for academic research, professional growth, and business training. Visit the AWS Disaster Response Hackathon to see what SageMaker Studio Lab is capable of. This event was designed to encourage machine learning solutions for important issues around disaster preparedness.

security across the board

Werner Vogels, vice president and chief technology officer of AWS, said that “Security is everyone’s duty” during one of the recent re:Invent conferences. Since then, it may seem as though there has been a decrease in the quantity of security-related sessions at re:Invent. But at re:Invent2021, security information was presented in almost every session.

At this year’s re:Invent, Access Analyzer Security was a key concern in almost every product, demo, and pipeline. AWS security service pillars were the subject of some outstanding presentations, including ones on IAM policies, KMS, and confidentiality. Access Analyzer, a free tool that customers may use to assess rules in AWS Organizations, included features in both of these deep dives. It’s one of those obvious, high-value technologies that everyone should use, similar to AWS CloudTrail. Users were guided by Brigid Johnson through the IAM introduction and how Access Analyzer fits in by determining safe access to resources using logic-based reasoning. If you are familiar with Brigid’s earlier work, you will notice that many horses and unicorns appeared in her demonstrations.

Additionally, Colm MacCarthaigh discussed how engineering teams and architecture procedures might assist you in treating customer data as radioactive. It’s not novel to use cryptographic controls to safeguard both the client and the company at the same time, but a lot of this technology is now more widely available and simpler to use than ever before. You can learn more about Datadog’s fantastic integration with IAM Access Analyzer here.

Observability at the forefront

It is evident that observability is a fundamental element in design and operations as environments get more complicated. Observability is being incorporated into the very DNA of the cloud services we develop because to tools like Datadog and strong open source standards like OpenTelemetry. Check out Matthew Williams and Shivansh Singh, a Senior Partner Solutions Architect at AWS, on telemetry and business metrics, as well as Rachel White on monitoring Amazon Elastic MapReduce workloads at scale, in addition to additional Datadog presentations at re:Invent 2021.

booth for Datadog at re:Invent 2021

No matter how re:Invent 2022 plays out, the concept of ever-more-mature goods will remain, and observability will undoubtedly continue to develop and expand. Our forecast is that this won’t only be helpful for operations; observability is probably going to become the key to identifying errors, assaults, and vulnerabilities across all of your environments. You may start keeping an eye on the security of your infrastructure here if you already use Datadog. If not, register for a 14-day free trial.