If you’re in a development or operations role, you probably gawked at this title. The truth is, having some other company manage your “DevOps” is an insult to the term. However, bear with me while I put out this scenario:
What if you don’t have a team that can manage all your tools that enable you to adopt DevOps methods?
Why should you have to spend time managing the tools you use, instead of developing and operating your application?
What if your team isn’t ready for this big cultural, process, and tooling change or disagrees on where to begin?
These are key reasons to consider adopting a DevOps platform managed by experts.
Just a Quick Definition:
To bring you along my thought process, let’s first agree on what DevOps IS. DevOps, a term built by combining the words Development and Operations, is a set of cultural values and organizational practices implemented with the intent to improve business outcomes. DevOps methods were initially formed to bridge the gap between Development and Operations so that teams could increase speed to delivery as well as quality of product at the same time. The focus of DevOps is to increase collaboration and feedback between Business Stakeholders, Development, QA, IT or Cloud Operations, and Security to build better products or services.
When companies attempt to adopt DevOps practices, they often think of tooling first. However, a true DevOps transformation includes an evolution of your company culture, processes, collaboration, measurement systems, organizational structure, and automation and tooling — in short, things that cannot be accomplished through automation alone.
Why DevOps? Adopting DevOps practices can be a gamechanger in your business if implemented correctly. Some of the benefits include:
Increase Operational Efficiencies – Simplify the software development toolchain and minimize re-work to reduce total cost of ownership.
Deliver Better Products Faster – Accelerate the software delivery process to quickly deliver value to your customers.
Reduce Security and Compliance Risk – Simplify processes to comply with internal controls and industry regulations without compromising speed.
Improve Product Quality, Reliability, and Performance – Limit context switching, reduce failures, and decrease MTTR while improving customer experience.
The basic goal here is to create and enable a culture of continuous improvement.
DevOps Is Not All Sunshine and Roses:
Despite the promise of DevOps, teams still struggle due to conflicting priorities and opposing goals, lackluster measurement systems, lack of communication or collaborative culture, technology sprawl creating unreliable systems, skill shortage, security bottlenecks, rework slowing progress…you get the picture. Even after attempting to solve these problems, many large enterprises face setbacks including:
Reliability: Their existing DevOps Toolchain is brittle, complex, and expensive to maintain.
Speed: Developers are slowed down by bottlenecks, hand-offs, and re-work.
Security: Security is slowing down their release cycle, but they still need to make sure they scan the code for licensing and vulnerabilities issues before it goes out.
Complexity: DevOps is complex and an ongoing process. They don’t currently have the internal skillset to start or continue their progress.
Enterprise Ready: SaaS DevOps offerings do not enable them to have privacy or features they require for enterprise security and management.
Enter Managed DevOps:
Managed DevOps removes much of this complexity by providing you with a proven framework for success beginning with an assessment that sets the go-forward strategy, working on team upskilling, implementing end-to-end tooling, and then finally providing ongoing management and coaching.
If you have these symptoms, Managed DevOps is the cure:
Non-Existent or Brittle Pipeline
Tools are a Time Suck; No time to focus on application features
You know change is necessary, but your team disagrees on where to begin
Because Managed DevOps helps bring your teams along the change curve by providing the key upskilling and support, plus a proven tool-chain, you can kick off immediately without spending months debating tooling or process.
If you’re ready to remove the painful complexity and start to build, test, and deploy applications in the cloud in a continuous and automated way, talk with our DevOps experts about implementing a Managed DevOps solution.
Are you facing pressure to make better decisions, faster? Are you uneasy about making too many gut-level business decisions? Are you being asked to have a data strategy from above and wondering how to compete in a data-driven world?
You are not alone. These are common themes emerging in today’s digital economy. Customers of all kinds – from consumers to enterprise businesses – have greater and greater choices than ever before. That means your customers are demanding more service, faster, and at a higher quality. How you decide to meet these needs is becoming very complex. You need to choose among many competing options. Increasingly, making these decisions by trusting your gut is a recipe for disaster!
These difficult decisions are not made any easier with the rise of Software as a Service (SaaS). While it’s easy to get up and going with SaaS offerings to handle business productivity needs, with every new SaaS offering you use, you end up silo-ing your data even more. Every department, every business function, has multiple data silos that make holistic business analysis an uphill climb. How can you tie together customer satisfaction and operations data, if the data is in two different systems?
Can you find the data you need? Once you find it, do you trust it? It just shouldn’t be this hard to make business decisions!
We know this is a common problem, because we hear it over and over again from our customers. We continue to hear about this problem, despite the relative maturity of “big data” systems. If big data has been a thing for at least two decades, why are we still struggling to make sense of it all? Our diagnosis is pretty simple:
Data projects that lack a business goal will fail, and most data projects lack a clear business goal, such as “increasing customer satisfaction.”
It’s hard to find people to do the hard work of connecting systems and pulling data out.
So, despite fantastic big data ecosystems being widely available, if you lack a clear business objective and you can’t assign people to roll up their sleeves and move data to where it needs to be, then unfortunately your data initiative will die on the vine.
Our solution to this is very straightforward:
We start with the business goal and never put it on the back burner. Our consultants are trained to listen for and capture business objectives from your team (and people around your team) and hang onto them tightly, while allowing flexibility when it comes to the implementation details. This is very rare in cloud consulting. Most cloud consultancies miss the business goals and skip straight to engineering. We think this is unacceptable and have seen it lead to purposeless, cash-hemorrhaging projects.
We then rapidly get to work and implement our best-practices DataOps solution. It’s pre-built, uses 100% serverless AWS offerings, and is battle-tested over dozens of successful deployments and years of incorporating AWS best practices. Since it is serverless, scaling your DataOps foundation to dozens or hundreds of data sources is painless.
Then, we connect your first several data sources, such as Salesforce, or logs, or customer data, or whatever we together have identified will support your business use case. This is the hard work of rolling up your sleeves, and we have the people to do it.
Within the first two weeks, most customers are analyzing data from multiple sources in a single pane of glass.
Finally, we make your analytics production-ready and help you share the good news around your organization.
These are the benefits that our customers have told us they have received.
You can make better, data-driven decisions. Since we start and end the engagement with your business focus in mind, you are able to make better, data-informed decisions. Where before you were trusting your gut, now you have real, relevant, current data to support your decision making. You’re not driving blind.
You can trust your dashboards and reports. Since we have implemented a best-practices Data Catalog, you have a crystal-clear picture of how your data got to its end state. You are not questioning “is this data real?” because you have clear traceability of data from source to metrics. If you can’t trust your data when you try to act on it, what’s the point?
Your analysis gets even better with yet more data sources. Now that you have a central data lake with easy-to-replicate patterns for bringing in new data, you can make your analyses even richer by adding yet more sources. Many of our customers enrich their data with a wide variety of internal sources, and even external sources like weather and macroeconomic data, to find new correlations and trends that were not possible before.
You feed a culture of DataOps. Word will get around that your team has the ability to drastically simplify data access and analysis because our DataOps Foundation comes with commonsense access rules right out of the box. It is not a threat to give access to the right people – it will help your business operate. This tends to have a flywheel effect. Other departments get excited and want to add their data; analyses get better and richer; then even more people want to bring in their data.
You are now AI-ready. If all the analytical benefits were not enough, you are now also ready for AI and machine learning (ML). It’s just not possible to perform any kind of AI with messy data. With our DataOps Solution, you have solved two problems at once – you have action-ready business data, and you have cleared the path for repeatable AI projects.
You are not alone if you still can’t get the data you need. If your data still feels invisible to you, and you don’t think it should be so hard to crunch data for business outcomes, then you should know that there is a better way. Our DataOps Solution puts your business goals front and center. Our straightforward engagement has you centralizing and analyzing data, in the cloud, securely, within a week or two. Then, you can add more sources to your heart’s content and enjoy the benefits of being data-driven and AI-ready in today’s demanding economy.
To get started, contact us to book a discussion and a demo.
-Rob Whelan, Practice Manager, Data Engineering & Analytics
2nd Watch helped Cherwell Software onboard to AWS Managed Services (AMS) to provide a holistic approach to SaaS architecture and improve their customer experience. When managing infrastructure was taking away from Cherwell’s product development processes, 2nd Watch served as a consulting partner in developing their strategy and engagement to onboarding to AMS quickly, enabling them to provide great service management experience to its customers.
Gartner says, “DevOps initiatives improve speed and agility, but monitoring often starts during production. To provide superior customer experiences, infrastructure and operations leaders need to build instrumentation into the preproduction phase, tracking metrics on availability, performance and service health.”
“How can I&O leaders leverage monitoring practices to continually improve DevOps deployments and performance against business key performance indicators (KPIs)? This research identifies monitoring practices that I&O leaders should embed in the preproduction phase of DevOps cycles to address needs across application development and release management.” says the report.
It’s easy to forget that when enterprises first started moving to the cloud, it was a largely simple process that saw only a handful of people within an organization using the technology. But as its usage has become more prevalent, on-site infrastructure and IT operations teams have found themselves having to manage cloud environments, which has not only created a skills gap in many enterprises, but also given rise to cost inefficiencies as teams have either become spread more thinly, or, more likely, organizations have had to hire additional staff to manage their cloud environments. All of this can be compounded by trying to successfully integrate a cloud environment into an existing operation’s security structure.
The good news is that as cloud offerings have developed, all of these challenges can be addressed by managed cloud services. They help remove additional costs by negating the need for additional staff, as well as removing the complexity of trying to run a cloud environment for a large enterprise that wants to focus on running its business rather than running its infrastructure.
As managed cloud services continue their reach into the mainstream, customers will need to be educated on the myriad benefits the offering presents. Services such as AWS Managed Services (AMS) can offer enterprises a much easier cloud experience that doesn’t have to impinge upon the day-to-day running of the business.
Why managed cloud?
For clients questioning why they would benefit from a managed cloud offering, the first thing to note is that there is a clear reduction in the operational costs of cloud to be found. Enterprises no longer have to hire staff or spend time training existing staff to manage their cloud infrastructure. Alongside this, with a managed cloud services offering, enterprises have direct access to a team with a high level of skill set in cloud services and who will handle that portion of the organization’s infrastructure. Aspects like logging, monitoring, event management, continuity management, security and access management, patching, provisioning, incidents and reporting are all included in a managed cloud service offering.
AMS in particular is a highly automated offering, meaning that implementation is straightforward and much quicker than regular cloud implementations. It also features out-of-the-box compliance, such as PCI, HIPAA and GDPR, meaning that security postures won’t be disrupted during or after implementation. The service’s automation also allows for requests for change to be done within minutes, versus having to wait for an in-house IT infrastructure team to approve something before it can be changed.
And managed cloud services can have a significant impact upon an enterprise’s operations. For example, one of our clients – an ISV – was experiencing considerable challenges when evolving its product into a SaaS offering. While it was able to service the product, it wasn’t able to service the cloud infrastructure hosting the SaaS product. Using a managed cloud service – in this case AMS – meant the organization no longer had to manage that infrastructure itself and has since been able to decrease its time to resolution, as well as its cost of operations.
Further, the change enabled the ISV to be able to better predict their cost of goods sold given that AMS is a relatively steady monthly statement. This allows ISVs to consistently measure margin on their SaaS product offering.
Making the move to AMS
Migrating to AMS from on-premise infrastructure or an existing AWS environment is a straightforward process that consists of four key stages:
Discovering what exists today and what needs to migrate
Identifying the architecture to migrate (single account or multi-account landing zone)
Identifying the migration plan (scheduled app migration in ‘waves’)
Migrating to AMS
For customers on alternative cloud infrastructures, such as Google Cloud or Microsoft Azure, the migration to AMS is similar. The only bit of heavy lifting (for customers on any cloud platform) can come in integrating an existing operations team with the AMS operations teams so that they know how to work together if there’s a request, an update, or a problem.
Preparing for and performing this people-and-process integration upfront considerably reduces the complexity of cloud operations. This merger of operations usually flows from discovery and doesn’t end until the migration has been tested and the team is operating efficiently.
The path to AMS is a very structured, concrete process, which means clients don’t have to make myriad new decisions on their own. The onboarding process is streamlined and enables us as AMS partners to provide a true timeline for onboarding – something that can often be difficult when you’re dealing with a very large cloud migration.
For example, with AMS we know that discovery and planning take about three weeks, and building out the AMS landing zone takes about three weeks, and you can’t run these steps concurrently. We’ve received client feedback telling us that offering these timescales has been key to their comfort in engaging with this process and knowing they can get it done – clients don’t want an open-ended project that takes six years to migrate.
When it comes down to it, the cloud goals for the majority of customers is to streamline business processes and, ultimately, improve their bottom line. Using a managed cloud service like AMS can reduce costs, reduce operational challenges and increase security, making for a much smoother and easier experience for the enterprise, and a lucrative, open-ended opportunity for channel partners.
-Contributed article by Stefana Muller, Sr Product Manager
AWS Outposts are fully managed and configurable compute and storage racks built with AWS-designed hardware that allow customers to run compute and storage on-premises, while seamlessly connecting to AWS’ broad array of services in the cloud. Here’s a deeper look at the service.
As an AWS Outposts Partner, 2nd Watch is able to help AWS customers overcome challenges that exist due to managing and supporting infrastructures both on-premises and in cloud environments and delivering positive outcomes at scale. Our team is dedicated to helping companies achieve their technology goals by leveraging the agility, breadth of services, and pace of innovation that AWS provides. Read more