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Streaming Wars: How Streaming Services Can Strengthen Infrastructure to Improve the User Experience

Amir Krayden
Senser

Following the release of Netflix's impressive fourth quarter earnings report, which highlighted a 12.5% increase in revenue and an additional 13 million subscribers from the previous year, one thing is for certain: we are in the heyday of video streaming services. As viewers continue to be glued to their screens to tune in to new content and rewatch their favorite shows, the industry is absolutely thriving — in 2021, Forbes reported close to 50 services in North America alone, and as of 2023, that number has climbed to 239 (according to IBISWorld).

But with over 200 streaming services to choose from, including multiple platforms featuring similar types of entertainment, users have little incentive to remain loyal to any given platform if it exhibits performance issues. Big names in streaming like Hulu, Amazon Prime and HBO Max invest thousands of hours into engineering observability and closed-loop monitoring to combat infrastructure and application issues, but smaller platforms struggle to remain competitive without access to the same resources.


Compounding the importance of reliability for brand loyalty is the need for streaming platforms to constantly innovate and outpace competitors; new UX and faster speeds are necessary to stand out from the pack. However, these new deployments can easily lead to unforeseen service issues unless proper monitoring is put in place.

Market Evolution

Combined with the standards set by industry leaders like Netflix, Hulu, Amazon Prime and HBO Max, our culture's heightened emphasis on and desire for instant gratification has raised the bar for customer expectations. Because of this, traditional infrastructure and application tools are no longer good enough. Existing solutions leave room for potential disruptions that go undetected and impact the user experience. To keep pace with the times, streaming services — especially ones of smaller scale — must invest in future-proofing observability solutions that combine real-time, zero-instrumentation topology of their environments with predictive analytics and machine learning to stay ahead of competitors and maintain the business of their customers.

How Smaller Streaming Companies Can Position Themselves to Win

Large streaming services such as Prime Video and Hulu invest thousands of hours into engineering observability and closed-loop monitoring. An example of this is Netflix's pioneering architecture and in-house tools, which have set the curve for the industry. But for the smaller streaming services, particularly newcomers to the AVOD and FAST spaces, scaling the many moving parts of a streaming platform becomes a challenge. The layers of infrastructure, network, storage and computation create interdependent systems that can lead to cascading effects and serious service disruptions. To secure their position within an increasingly crowded space, it's essential for streaming services to build strong observability.

To ensure that they are best positioned to mitigate and quickly respond to anything that could result in a service disruption, it is important for all streaming services to have the resources in place to allow them to scale and strengthen the layers of technology that are critical to their continued operations and efficiency.

For smaller and newer streaming services looking to scale operations — and deploy increasingly complicated infrastructure and networking — it's essential to understand the interdependencies of different systems, services, and data centers. Rather than attempt to cobble these solutions together in-house with limited resources, streamers can take advantage of the growing AIOps for observability space, and make use of both vendors and open-source tools.

Key Factors to Consider

When exploring the option to onboard next-gen observability tools, smaller streaming platforms should consider the following elements:

The "hidden costs" of observability — Paying for a third-party service is often cheaper than the ballooning costs of attempting to monitor in-house, or use legacy solutions. Traditional monitoring tools can eat up a significant portion of infrastructure budgets, as high as 30%.

Getting DevOps back to important feature work — as mentioned above, staying ahead of the competition is essential in the streaming space. If DevOps teams are burdened by triaging and analyzing production issues, they're unable to work on new feature developments — such as improved UX — that will help their organization get ahead of the competition.

Streaming services are very sensitive in terms of their entire stack — infrastructure, network and video layers all comprise a delicate ecosystem, wherein a production issue has a compounded risk to affect customers. A full-stack holistic approach to observability is a must.

By ensuring that their IT infrastructure and environments are well-equipped with the tools and capabilities necessary to maintain smooth service to users, smaller streaming platforms can position themselves to uphold important operations and be able to keep pace with a market dominated by industry leaders.

Amir Krayden is CEO and Co-Founder of Senser

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Streaming Wars: How Streaming Services Can Strengthen Infrastructure to Improve the User Experience

Amir Krayden
Senser

Following the release of Netflix's impressive fourth quarter earnings report, which highlighted a 12.5% increase in revenue and an additional 13 million subscribers from the previous year, one thing is for certain: we are in the heyday of video streaming services. As viewers continue to be glued to their screens to tune in to new content and rewatch their favorite shows, the industry is absolutely thriving — in 2021, Forbes reported close to 50 services in North America alone, and as of 2023, that number has climbed to 239 (according to IBISWorld).

But with over 200 streaming services to choose from, including multiple platforms featuring similar types of entertainment, users have little incentive to remain loyal to any given platform if it exhibits performance issues. Big names in streaming like Hulu, Amazon Prime and HBO Max invest thousands of hours into engineering observability and closed-loop monitoring to combat infrastructure and application issues, but smaller platforms struggle to remain competitive without access to the same resources.


Compounding the importance of reliability for brand loyalty is the need for streaming platforms to constantly innovate and outpace competitors; new UX and faster speeds are necessary to stand out from the pack. However, these new deployments can easily lead to unforeseen service issues unless proper monitoring is put in place.

Market Evolution

Combined with the standards set by industry leaders like Netflix, Hulu, Amazon Prime and HBO Max, our culture's heightened emphasis on and desire for instant gratification has raised the bar for customer expectations. Because of this, traditional infrastructure and application tools are no longer good enough. Existing solutions leave room for potential disruptions that go undetected and impact the user experience. To keep pace with the times, streaming services — especially ones of smaller scale — must invest in future-proofing observability solutions that combine real-time, zero-instrumentation topology of their environments with predictive analytics and machine learning to stay ahead of competitors and maintain the business of their customers.

How Smaller Streaming Companies Can Position Themselves to Win

Large streaming services such as Prime Video and Hulu invest thousands of hours into engineering observability and closed-loop monitoring. An example of this is Netflix's pioneering architecture and in-house tools, which have set the curve for the industry. But for the smaller streaming services, particularly newcomers to the AVOD and FAST spaces, scaling the many moving parts of a streaming platform becomes a challenge. The layers of infrastructure, network, storage and computation create interdependent systems that can lead to cascading effects and serious service disruptions. To secure their position within an increasingly crowded space, it's essential for streaming services to build strong observability.

To ensure that they are best positioned to mitigate and quickly respond to anything that could result in a service disruption, it is important for all streaming services to have the resources in place to allow them to scale and strengthen the layers of technology that are critical to their continued operations and efficiency.

For smaller and newer streaming services looking to scale operations — and deploy increasingly complicated infrastructure and networking — it's essential to understand the interdependencies of different systems, services, and data centers. Rather than attempt to cobble these solutions together in-house with limited resources, streamers can take advantage of the growing AIOps for observability space, and make use of both vendors and open-source tools.

Key Factors to Consider

When exploring the option to onboard next-gen observability tools, smaller streaming platforms should consider the following elements:

The "hidden costs" of observability — Paying for a third-party service is often cheaper than the ballooning costs of attempting to monitor in-house, or use legacy solutions. Traditional monitoring tools can eat up a significant portion of infrastructure budgets, as high as 30%.

Getting DevOps back to important feature work — as mentioned above, staying ahead of the competition is essential in the streaming space. If DevOps teams are burdened by triaging and analyzing production issues, they're unable to work on new feature developments — such as improved UX — that will help their organization get ahead of the competition.

Streaming services are very sensitive in terms of their entire stack — infrastructure, network and video layers all comprise a delicate ecosystem, wherein a production issue has a compounded risk to affect customers. A full-stack holistic approach to observability is a must.

By ensuring that their IT infrastructure and environments are well-equipped with the tools and capabilities necessary to maintain smooth service to users, smaller streaming platforms can position themselves to uphold important operations and be able to keep pace with a market dominated by industry leaders.

Amir Krayden is CEO and Co-Founder of Senser

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Developers building AI applications are not just looking for fault patterns after deployment; they must detect issues quickly during development and have the ability to prevent issues after going live. Unfortunately, traditional observability tools can no longer meet the needs of AI-driven enterprise application development. AI-powered detection and auto-remediation tools designed to keep pace with rapid development are now emerging to proactively manage performance and prevent downtime ...

Every few years, the cybersecurity industry adopts a new buzzword. "Zero Trust" has endured longer than most — and for good reason. Its promise is simple: trust nothing by default, verify everything continuously. Yet many organizations still hesitate to implement Zero Trust Network Access (ZTNA). The problem isn't that ZTNA doesn't work. It's that it's often misunderstood ...

For many retail brands, peak season is the annual stress test of their digital infrastructure. It's also when often technical dashboards glow green, yet customer feedback, digital experience frustration, and conversion trends tell a different story entirely. Over the past several years, we've seen the same pattern across retail, financial services, travel, and media: internal application performance metrics fail to capture the true experience of users connecting over local broadband, mobile carriers, and congested networks using multiple devices across geographies ...

PostgreSQL promises greater flexibility, performance, and cost savings compared to proprietary alternatives. But successfully deploying it isn't always straightforward, and there are some hidden traps along the way that even seasoned IT leaders can stumble into. In this blog, I'll highlight five of the most common pitfalls with PostgreSQL deployment and offer guidance on how to avoid them, along with the best path forward ...

The rise of hybrid cloud environments, the explosion of IoT devices, the proliferation of remote work, and advanced cyber threats have created a monitoring challenge that traditional approaches simply cannot meet. IT teams find themselves drowning in a sea of data, struggling to identify critical threats amidst a deluge of alerts, and often reacting to incidents long after they've begun. This is where AI and ML are leveraged ...

Three practices, chaos testing, incident retrospectives, and AIOps-driven monitoring, are transforming platform teams from reactive responders into proactive builders of resilient, self-healing systems. The evolution is not just technical; it's cultural. The modern platform engineer isn't just maintaining infrastructure. They're product owners designing for reliability, observability, and continuous improvement ...

Getting applications into the hands of those who need them quickly and securely has long been the goal of a branch of IT often referred to as End User Computing (EUC). Over recent years, the way applications (and data) have been delivered to these "users" has changed noticeably. Organizations have many more choices available to them now, and there will be more to come ... But how did we get here? Where are we going? Is this all too complicated? ...

On November 18, a single database permission change inside Cloudflare set off a chain of failures that rippled across the Internet. Traffic stalled. Authentication broke. Workers KV returned waves of 5xx errors as systems fell in and out of sync. For nearly three hours, one of the most resilient networks on the planet struggled under the weight of a change no one expected to matter ... Cloudflare recovered quickly, but the deeper lesson reaches far beyond this incident ...

Chris Steffen and Ken Buckler from EMA discuss the Cloudflare outage and what availability means in the technology space ...

Every modern industry is confronting the same challenge: human reaction time is no longer fast enough for real-time decision environments. Across sectors, from financial services to manufacturing to cybersecurity and beyond, the stakes mirror those of autonomous vehicles — systems operating in complex, high-risk environments where milliseconds matter ...