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Web Performance and the Impact of SPDY, HTTP/2 & QUIC - Part 2

Jean Tunis

This blog is the second in a 5-part series on APMdigest where I discuss web application performance and how new protocols like SPDY, HTTP/2, and QUIC will hopefully improve it so we can have happy website users.

Start with Web Performance 101: The Bandwidth Myth

Start with Web Performance 101: 4 Recommendations to Improve Web Performance

Start with Web Performance and the Impact of SPDY, HTTP/2 & QUIC - Part 1

The HyperText Transport Protocol (HTTP) is the application layer protocol in the TCP/IP stack used for the communication of web traffic. The current version that has been ratified by Internet Engineering Task Force (IETF) is HTTP/2 (more on that later), and it happened in May 2015.

But the most widely used version is the previous version, HTTP/1.1.

According to the HTTP/2 Dashboard, only about 4% of the top 2 million Alexa sites truly support HTTP/2. So we still have a ways to go.

Ratified almost 20 years ago in 1997, HTTP/1.1 was meant to address two big limitations in the previous HTTP/1.0.

HTTP/1.0 Limitations

One limitation was a lack of persistent connections. With 1.0, every HTTP request required opening up a new TCP connection. As mentioned in my previous blog, this requires resources and introduces additional latency.

Another limitation was being able to send multiple requests at one time without needing any responses from the other side. The ability to pipeline requests in HTTP/1.1 was meant to address this.

But as the web continued to advance, it became clear that HTTP/1.1 still had many limitations that needed to be worked on.

HTTP/1.1 Limitations

1.1 has a number of limitations, but I want to talk about three of them that has been issues over the years.

Many small requests makes HTTP/1.1 latency sensitive

With images, HTML files, CSS files, JS files, and many others, HTTP transfers a lot of requests. Many of these requests are short-lived with files that can be on the order of tens of KBs.

But the same process happens each time a new connection is made, and many steps occur every time a new request on the same connection is made. Things like a DNS query, packet propagation from the browser to the server and back, encryption, compression, etc. All these things require time across the network, no matter how small.

So all these little requests introduce latency, thereby making HTTP latency-sensitive.

Pipelining is not multiplexing

Pipelining was supposed to address a limitation in HTTP/1.0. But over the years, we've seen that in HTTP/1.1, it caused other limitations itself.

For one, no matter how many requests were pipelined, the server still was required to respond to each request in order. So if one of those requests got to the server out of the order it was sent, and arrived later, the server could not respond to the other that got there earlier. It had to wait for the out-of-order request before replying to the others.

Two, the nature of the TCP protocol is such that segmentation and reassembly of data occurred in proper order. Due to how the protocol operates, any segments at the head of a stream of segments had to be processed first. This caused the TCP head-of-line blocking.

Because of these limitations, most modern browsers disabled pipelining, thus, obviously defeating the purpose of having it in place as part of the standard.

Short-lived requests affected by TCP slow start

As a connection-oriented protocol, TCP ensures delivery of each and every piece of data it sends. In the early days of the Internet, we didn't have a lot of bandwidth, by today's standard anyway. Remember 56K modems? TCP was designed at a time before then.

To prevent applications from overwhelming the network, and jeopardizing TCP's operations, the concept of a slow-start was introduced in RFC 1122. This ensured that the application would start with sending a little bit of data to the server, initially 1 MSS, wait until it gets an ACK, and then gradually send more data via the congestion window until it gets to the maximum advertised window size.

Years ago, the default number of segments (or congestion window size) was 3. With the default TCP maximum segment size (MSS) being 1,460 bytes, it means that the maximum amount of data that could be sent at one time was only about 4KB.

HTTP requests were small, but not that small. And since HTTP requests often don't last very long, this meant that many requests never got out of TCP slow start before the connection was no longer required.

Since then, the initial congestion window size was increased to 10 segments, or almost 15KB. A paper published by Google in 2010 showed that 10 segments is the sweet spot to maximize throughput and response time. This has become part of RFC 6928.

Read Web Performance and the Impact of SPDY, HTTP/2 & QUIC - Part 3, covering common HTTP/1.1 workarounds, SPDY and HTTP/2.

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Web Performance and the Impact of SPDY, HTTP/2 & QUIC - Part 2

Jean Tunis

This blog is the second in a 5-part series on APMdigest where I discuss web application performance and how new protocols like SPDY, HTTP/2, and QUIC will hopefully improve it so we can have happy website users.

Start with Web Performance 101: The Bandwidth Myth

Start with Web Performance 101: 4 Recommendations to Improve Web Performance

Start with Web Performance and the Impact of SPDY, HTTP/2 & QUIC - Part 1

The HyperText Transport Protocol (HTTP) is the application layer protocol in the TCP/IP stack used for the communication of web traffic. The current version that has been ratified by Internet Engineering Task Force (IETF) is HTTP/2 (more on that later), and it happened in May 2015.

But the most widely used version is the previous version, HTTP/1.1.

According to the HTTP/2 Dashboard, only about 4% of the top 2 million Alexa sites truly support HTTP/2. So we still have a ways to go.

Ratified almost 20 years ago in 1997, HTTP/1.1 was meant to address two big limitations in the previous HTTP/1.0.

HTTP/1.0 Limitations

One limitation was a lack of persistent connections. With 1.0, every HTTP request required opening up a new TCP connection. As mentioned in my previous blog, this requires resources and introduces additional latency.

Another limitation was being able to send multiple requests at one time without needing any responses from the other side. The ability to pipeline requests in HTTP/1.1 was meant to address this.

But as the web continued to advance, it became clear that HTTP/1.1 still had many limitations that needed to be worked on.

HTTP/1.1 Limitations

1.1 has a number of limitations, but I want to talk about three of them that has been issues over the years.

Many small requests makes HTTP/1.1 latency sensitive

With images, HTML files, CSS files, JS files, and many others, HTTP transfers a lot of requests. Many of these requests are short-lived with files that can be on the order of tens of KBs.

But the same process happens each time a new connection is made, and many steps occur every time a new request on the same connection is made. Things like a DNS query, packet propagation from the browser to the server and back, encryption, compression, etc. All these things require time across the network, no matter how small.

So all these little requests introduce latency, thereby making HTTP latency-sensitive.

Pipelining is not multiplexing

Pipelining was supposed to address a limitation in HTTP/1.0. But over the years, we've seen that in HTTP/1.1, it caused other limitations itself.

For one, no matter how many requests were pipelined, the server still was required to respond to each request in order. So if one of those requests got to the server out of the order it was sent, and arrived later, the server could not respond to the other that got there earlier. It had to wait for the out-of-order request before replying to the others.

Two, the nature of the TCP protocol is such that segmentation and reassembly of data occurred in proper order. Due to how the protocol operates, any segments at the head of a stream of segments had to be processed first. This caused the TCP head-of-line blocking.

Because of these limitations, most modern browsers disabled pipelining, thus, obviously defeating the purpose of having it in place as part of the standard.

Short-lived requests affected by TCP slow start

As a connection-oriented protocol, TCP ensures delivery of each and every piece of data it sends. In the early days of the Internet, we didn't have a lot of bandwidth, by today's standard anyway. Remember 56K modems? TCP was designed at a time before then.

To prevent applications from overwhelming the network, and jeopardizing TCP's operations, the concept of a slow-start was introduced in RFC 1122. This ensured that the application would start with sending a little bit of data to the server, initially 1 MSS, wait until it gets an ACK, and then gradually send more data via the congestion window until it gets to the maximum advertised window size.

Years ago, the default number of segments (or congestion window size) was 3. With the default TCP maximum segment size (MSS) being 1,460 bytes, it means that the maximum amount of data that could be sent at one time was only about 4KB.

HTTP requests were small, but not that small. And since HTTP requests often don't last very long, this meant that many requests never got out of TCP slow start before the connection was no longer required.

Since then, the initial congestion window size was increased to 10 segments, or almost 15KB. A paper published by Google in 2010 showed that 10 segments is the sweet spot to maximize throughput and response time. This has become part of RFC 6928.

Read Web Performance and the Impact of SPDY, HTTP/2 & QUIC - Part 3, covering common HTTP/1.1 workarounds, SPDY and HTTP/2.

Hot Topics

The Latest

In MEAN TIME TO INSIGHT Episode 24, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses network observability tool sprawl ... 

In cloud-native systems, scaling is often as simple as moving a slider. For on-premise databases, the stakes are different. Over-provisioning hardware is expensive. Under-provisioning leads to performance bottlenecks that are difficult to fix once the equipment is in the rack ...

When most people think about cybersecurity, they picture firewalls, encryption, and access controls — technical tools designed to protect systems and data. But beneath the technology lies a deeper set of principles about trust, decision-making, and resilience ... The best leaders don't eliminate risk. They manage it intelligently. And in many ways, cybersecurity offers a surprisingly useful playbook for doing exactly that ...

Many organizations assumed their infrastructure strategy was settled. It had been implemented, optimized and built into long-term plans. Recent changes in technology and vendor consolidation are forcing a second look. Cloud outages and licensing changes have exposed how much dependency exists on a small number of platforms. As a result, organizations are reevaluating whether those decisions still hold up under current conditions ...

Edge AI is strategically embedded in core IT and infrastructure spending across industries, according to the 2026 Edge AI Survey from ZEDEDA. The research shows that 83% of C-suite and IT executive respondents say edge AI is important to their core business strategy ...

As AI adoption accelerates, operational complexity — not model intelligence — is becoming the primary barrier to reliable AI at scale, according to the State of AI Engineering 2026 from Datadog ... The report highlights a compounding complexity challenge as AI systems scale ... Around 5% of AI model requests fail in production, with nearly 60% of those failures caused by capacity limits ...

For years, production operations teams have treated alert fatigue as a quality-of-life problem: something that makes on-call rotations miserable but isn't considered a direct contributor to outages. That framing doesn't capture how these systems fail, and we now have data to show why. More importantly, it's now clear alert fatigue is a symptom of a deeper issue: production systems have outgrown the current operational approaches ...

I was on a customer call last fall when an enterprise architect said something I haven't been able to shake. Her team had just spent four months trying to swap one AI vendor for another. The original plan said three weeks. "We didn't switch vendors," she told me. "We rebuilt half our integrations and discovered what we'd actually been depending on." Most enterprise leaders don't expect that to be the experience ...

Ask any senior SRE or platform engineer what keeps them up at night, and the answer probably isn't the monitoring tool — it's the data feeding it. The proliferation of APM, observability, and AIOps platforms has created a telemetry sprawl problem that most teams manage reactively rather than architect proactively. Metrics are going to one platform. Traces routed somewhere else. Logs duplicated across multiple backends because nobody wants to be caught without them when something breaks. Every redundant stream costs money ...

80% of respondents agree that the IT role is shifting from operators to orchestrators, according to the 2026 IT Trends Report: The Human Side of Autonomous IT from SolarWinds ...